subject:(Depth estimation)

University of Adelaide

1. Cao, Yuanzhouhan. Deep learning based RGB-D vision tasks.

Degree: 2018, University of Adelaide

► Depth is an important source of information in computer vision. However, depth is usually discarded in most vision tasks. In this thesis, we study the… (more)

Subjects/Keywords: depth estimation; object detection; semantic segmentation

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Cao, Y. (2018). Deep learning based RGB-D vision tasks. (Thesis). University of Adelaide. Retrieved from http://hdl.handle.net/2440/112866

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Cao, Yuanzhouhan. “Deep learning based RGB-D vision tasks.” 2018. Thesis, University of Adelaide. Accessed August 23, 2019. http://hdl.handle.net/2440/112866.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Cao, Yuanzhouhan. “Deep learning based RGB-D vision tasks.” 2018. Web. 23 Aug 2019.

Vancouver:

Cao Y. Deep learning based RGB-D vision tasks. [Internet] [Thesis]. University of Adelaide; 2018. [cited 2019 Aug 23]. Available from: http://hdl.handle.net/2440/112866.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Cao Y. Deep learning based RGB-D vision tasks. [Thesis]. University of Adelaide; 2018. Available from: http://hdl.handle.net/2440/112866

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Universitat Autònoma de Barcelona

2. Cheda, Diego. Monocular Depth Cues in Computer Vision Applications.

Degree: Departament de Ciències de la Computació, 2012, Universitat Autònoma de Barcelona

URL: http://hdl.handle.net/10803/121644

► Depth perception is a key aspect of human vision. It is a routine and essential visual task that the human do effortlessly in many daily… (more)

▼ Depth perception is a key aspect of human vision. It is a routine and essential visual task that the human do effortlessly in many daily activities. This has often been associated with stereo vision, but humans have an amazing ability to perceive depth relations even from a single image by using several monocular cues. In the computer vision field, if image depth information were available, many tasks could be posed from a different perspective for the sake of higher performance and robustness. Nevertheless, given a single image, this possibility is usually discarded, since obtaining depth information has frequently been performed by three-dimensional reconstruction techniques, requiring two or more images of the same scene taken from different viewpoints. Recently, some proposals have shown the feasibility of computing depth information from single images. In essence, the idea is to take advantage of a priori knowledge of the acquisition conditions and the observed scene to estimate depth from monocular pictorial cues. These approaches try to precisely estimate the scene depth maps by employing computationally demanding techniques. However, to assist many computer vision algorithms, it is not really necessary computing a costly and detailed depth map of the image. Indeed, just a rough depth description can be very valuable in many problems. In this thesis, we have demonstrated how coarse depth information can be integrated in different tasks following holistic and alternative strategies to obtain more precise and robustness results. In that sense, we have proposed a simple, but reliable enough technique, whereby image scene regions are categorized into discrete depth ranges to build a coarse depth map. Based on this representation, we have explored the potential usefulness of our method in three application domains from novel viewpoints: camera rotation parameters estimation, background estimation and pedestrian candidate generation. In the first case, we have computed camera rotation mounted in a moving vehicle from two novels methods that identify distant elements in the image, where the translation component of the image flow field is negligible. In background estimation, we have proposed a novel method to reconstruct the background by penalizing close regions in a cost function, which integrates color, motion, and depth terms. Finally, we have benefited of geometric and depth information available on single images for pedestrian candidate generation to significantly reduce the number of generated windows to be further processed by a pedestrian classifier. In all cases, results have shown that our depth-based approaches contribute to better performances. Advisors/Committee Members: [email protected] (authoremail), true (authoremailshow), Ponsa Mussarra, Daniel (director), López Peña, Antonio M. (Antonio Manuel) (codirector), true (authorsendemail).

Subjects/Keywords: Monocular depth cues; Computer vision; Depth estimation; Tecnologies; 62

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Cheda, D. (2012). Monocular Depth Cues in Computer Vision Applications. (Thesis). Universitat Autònoma de Barcelona. Retrieved from http://hdl.handle.net/10803/121644

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Cheda, Diego. “Monocular Depth Cues in Computer Vision Applications.” 2012. Thesis, Universitat Autònoma de Barcelona. Accessed August 23, 2019. http://hdl.handle.net/10803/121644.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Cheda, Diego. “Monocular Depth Cues in Computer Vision Applications.” 2012. Web. 23 Aug 2019.

Vancouver:

Cheda D. Monocular Depth Cues in Computer Vision Applications. [Internet] [Thesis]. Universitat Autònoma de Barcelona; 2012. [cited 2019 Aug 23]. Available from: http://hdl.handle.net/10803/121644.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Cheda D. Monocular Depth Cues in Computer Vision Applications. [Thesis]. Universitat Autònoma de Barcelona; 2012. Available from: http://hdl.handle.net/10803/121644

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Australian National University

3. Qiu, Jiayan. Convolutional Neural Network based Age Estimation from Facial Image and Depth Prediction from Single Image .

Degree: 2016, Australian National University

URL: http://hdl.handle.net/1885/102510

► Convolutional neural network (CNN), one of the most commonly used deep learning methods, has been applied to various computer vision and pattern recognition tasks, and… (more)

▼ Convolutional neural network (CNN), one of the most commonly used deep learning methods, has been applied to various computer vision and pattern recognition tasks, and has achieved state-of-the-art performance. Most recent research work on CNN focuses on the innovations of the structure. This thesis explores both the innovation of structure and final label encoding of CNN. To evaluate the performance of our proposed network structure and label encoding method, two computer vision tasks are conducted, namely age estimation from facial image and depth estimation from a single image. For age estimation from facial image, we propose a novel hierarchical aggregation based deep network to learn aging features from facial images and apply our encoding method to transfer the discrete aging labels into a possibility label, which enables the CNN to conduct a classification task rather than regression task. In contrast to traditional aging features, where identical filter is applied to the en- tire facial image, our deep aging feature can capture both local and global cues in aging. Under our formulation, convolutional neural network (CNN) is employed to extract region specific features at lower layers. Then, low layer features are hierarchically aggregated by using fully connected way to consecutive higher layers. The resultant aging feature is of dimensionality 110, which achieves both good discriminative ability and efficiency. Experimental results of age prediction on the MORPH-II and the FG-NET databases show that the proposed deep aging feature outperforms state-of-the-art aging features by a margin. Depth estimation from a single image is an essential component toward understanding the 3D geometry of a scene. Compared with depth estimation from stereo images, depth map estimation from a single image is an extremely challenging task. This thesis addresses this task by regression with deep features, combined with surface normal constrained depth refinement. The proposed framework consists of two steps. First, we implement a convolutional neural network (CNN) to learn the mapping from multi-scale image patches to depth on the super-pixel level. In this step, we apply the proposed label encoding method to transfer the continuous depth labels to be possibility vectors, which reformulates the regression task to a classification task. Second, we refine predicted depth at the super-pixel level to the pixel level by exploiting surface normal constraints on depth map. Experimental results of depth estimation on the NYU2 dataset show that the proposed method achieves a promising performance and has a better performance compared with methods without the proposed label encoding. The above tasks show the proposed label encoding method has promising performance, which is another direction of CNN …

Subjects/Keywords: Convolutional Neural Network; Deep Learning; Computer Vision; Age Estimation; Depth Estimation

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Qiu, J. (2016). Convolutional Neural Network based Age Estimation from Facial Image and Depth Prediction from Single Image . (Thesis). Australian National University. Retrieved from http://hdl.handle.net/1885/102510

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Qiu, Jiayan. “Convolutional Neural Network based Age Estimation from Facial Image and Depth Prediction from Single Image .” 2016. Thesis, Australian National University. Accessed August 23, 2019. http://hdl.handle.net/1885/102510.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Qiu, Jiayan. “Convolutional Neural Network based Age Estimation from Facial Image and Depth Prediction from Single Image .” 2016. Web. 23 Aug 2019.

Vancouver:

Qiu J. Convolutional Neural Network based Age Estimation from Facial Image and Depth Prediction from Single Image . [Internet] [Thesis]. Australian National University; 2016. [cited 2019 Aug 23]. Available from: http://hdl.handle.net/1885/102510.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Qiu J. Convolutional Neural Network based Age Estimation from Facial Image and Depth Prediction from Single Image . [Thesis]. Australian National University; 2016. Available from: http://hdl.handle.net/1885/102510

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

IUPUI

4. Emerson, David R. 3-D Scene Reconstruction for Passive Ranging Using Depth from Defocus and Deep Learning.

Degree: 2019, IUPUI

URL: http://hdl.handle.net/1805/19900

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Indiana University-Purdue University Indianapolis (IUPUI)

Depth estimation is increasingly becoming more important in computer vision. The requirement for autonomous systems to gauge their surroundings is… (more)

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Indiana University-Purdue University Indianapolis (IUPUI)

Depth estimation is increasingly becoming more important in computer vision. The requirement for autonomous systems to gauge their surroundings is of the utmost importance in order to avoid obstacles, preventing damage to itself and/or other systems or people. Depth measuring/estimation systems that use multiple cameras from multiple views can be expensive and extremely complex. And as these autonomous systems decrease in size and available power, the supporting sensors required to estimate depth must also shrink in size and power consumption. This research will concentrate on a single passive method known as Depth from Defocus (DfD), which uses an in-focus and out-of-focus image to infer the depth of objects in a scene. The major contribution of this research is the introduction of a new Deep Learning (DL) architecture to process the the in-focus and out-of-focus images to produce a depth map for the scene improving both speed and performance over a range of lighting conditions. Compared to the previous state-of-the-art multi-label graph cuts algorithms applied to the synthetically blurred dataset the DfD-Net produced a 34.30% improvement in the average Normalized Root Mean Square Error (NRMSE). Similarly the DfD-Net architecture produced a 76.69% improvement in the average Normalized Mean Absolute Error (NMAE). Only the Structural Similarity Index (SSIM) had a small average decrease of 2.68% when compared to the graph cuts algorithm. This slight reduction in the SSIM value is a result of the SSIM metric penalizing images that appear to be noisy. In some instances the DfD-Net output is mottled, which is interpreted as noise by the SSIM metric. This research introduces two methods of deep learning architecture optimization. The first method employs the use of a variant of the Particle Swarm Optimization (PSO) algorithm to improve the performance of the DfD-Net architecture. The PSO algorithm was able to find a combination of the number of convolutional filters, the size of the filters, the activation layers used, the use of a batch normalization layer between filters and the size of the input image used during training to produce a network architecture that resulted in an average NRMSE that was approximately 6.25% better than the baseline DfD-Net average NRMSE. This optimized architecture also resulted in an average NMAE that was 5.25% better than the baseline DfD-Net average NMAE. Only the SSIM metric did not see a gain in performance, dropping by 0.26% when compared to the baseline DfD-Net average SSIM value. The second method illustrates the use of a Self Organizing Map clustering method to reduce the number convolutional filters in the DfD-Net to reduce the overall run time of the architecture while still retaining the network performance exhibited prior to the reduction. This method produces a reduced DfD-Net architecture that has a run time decrease of between 14.91% and 44.85% depending on the hardware architecture that…

Advisors/Committee Members: Christopher, Lauren A., Ben Miled, Zina, King, Brian, Salama, Paul.

Subjects/Keywords: Depth estimation; Deep Learning; Depth from Focus; Microfluidic Lens; LIDAR; Particle Swarm Optimization (PSO)

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Emerson, D. R. (2019). 3-D Scene Reconstruction for Passive Ranging Using Depth from Defocus and Deep Learning. (Thesis). IUPUI. Retrieved from http://hdl.handle.net/1805/19900

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Emerson, David R. “3-D Scene Reconstruction for Passive Ranging Using Depth from Defocus and Deep Learning.” 2019. Thesis, IUPUI. Accessed August 23, 2019. http://hdl.handle.net/1805/19900.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Emerson, David R. “3-D Scene Reconstruction for Passive Ranging Using Depth from Defocus and Deep Learning.” 2019. Web. 23 Aug 2019.

Vancouver:

Emerson DR. 3-D Scene Reconstruction for Passive Ranging Using Depth from Defocus and Deep Learning. [Internet] [Thesis]. IUPUI; 2019. [cited 2019 Aug 23]. Available from: http://hdl.handle.net/1805/19900.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Emerson DR. 3-D Scene Reconstruction for Passive Ranging Using Depth from Defocus and Deep Learning. [Thesis]. IUPUI; 2019. Available from: http://hdl.handle.net/1805/19900

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

KTH

5. Möckelind, Christoffer. Improving deep monocular depth predictions using dense narrow field of view depth images.

Degree: RPL, 2018, KTH

URL: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-235660

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In this work we study a depth prediction problem where we provide a narrow field of view depth image and a wide field of… (more)

Subjects/Keywords: Deep learning; Monocular; Depth estimation; Narrow field of view; RGB; RGBD; Noicy depth; Dense depth; Narrow depth; Sparse depth; Computer Sciences; Datavetenskap (datalogi)

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Möckelind, C. (2018). Improving deep monocular depth predictions using dense narrow field of view depth images. (Thesis). KTH. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-235660

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Möckelind, Christoffer. “Improving deep monocular depth predictions using dense narrow field of view depth images.” 2018. Thesis, KTH. Accessed August 23, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-235660.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Möckelind, Christoffer. “Improving deep monocular depth predictions using dense narrow field of view depth images.” 2018. Web. 23 Aug 2019.

Vancouver:

Möckelind C. Improving deep monocular depth predictions using dense narrow field of view depth images. [Internet] [Thesis]. KTH; 2018. [cited 2019 Aug 23]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-235660.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Möckelind C. Improving deep monocular depth predictions using dense narrow field of view depth images. [Thesis]. KTH; 2018. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-235660

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Princeton University

6. Yu, Fu. Pixel-Level Prediction: From Geometry to Semantics .

Degree: PhD, 2018, Princeton University

URL: http://arks.princeton.edu/ark:/88435/dsp018k71nk79v

► Pixel-level prediction generalizes a wide range of computer vision tasks including semantic image segmentation and dense depth prediction. They are fundamental for image recognition, receiving… (more)

▼ Pixel-level prediction generalizes a wide range of computer vision tasks including semantic image segmentation and dense depth prediction. They are fundamental for image recognition, receiving continual attention from the community. However, although they share common traits that may admit a general solution, they are usually studied in isolation because of different domain characteristics. This thesis aims to study the essential problems behind those tasks and shed light on a general framework. This thesis starts with an algorithm that can predict plausible depth from almost identical images based on geometric optimization. The motion between those images is called "Accidental Motion". The analysis of accidental motion shows that motion optimization has special convexity properties. It leads to a reconstruction pipeline that can produce a plausible dense depth map for the reference image, which is shown to enable depth based camera effects. The second part then studies learning pixel representation to predict semantic properties based on the single reference image. Previous works usually use learned upsampling to recover the pixel-level information. This work proposes to use Dilated Convolution to transform the classification networks such that high-resolution prediction is achieved without upsampling. Dilated Convolution can also render an exponential increase in receptive field, which is ideal for learning global context. A context module is proposed based on this property that can improve the network performance significantly and consistently. Dilation is still a standard component in the state-of-the-art method for semantic image segmentation. The further study of dilated residual networks shows that same high-resolution prediction can also improve image classification results. This indicates no essential network architecture difference exists between image classification and segmentation. Further inspection of class activation maps and layer responses uncover peculiar gridding patterns and their cause. This finding leads to new designs of convolutional networks that can remove the gridding artifacts and produce activations with better spatial consistency. The new networks can improve the performance of both image classification and semantic segmentation. The presented method and results may inspire new research in building a unified framework for image recognition of geometry and semantics. Advisors/Committee Members: Funkhouser, Thomas A (advisor).

Subjects/Keywords: convolutional networks; deep learning; depth estimation; dilated convolution; semantic segmentation

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Yu, F. (2018). Pixel-Level Prediction: From Geometry to Semantics . (Doctoral Dissertation). Princeton University. Retrieved from http://arks.princeton.edu/ark:/88435/dsp018k71nk79v

Chicago Manual of Style (16^th Edition):

Yu, Fu. “Pixel-Level Prediction: From Geometry to Semantics .” 2018. Doctoral Dissertation, Princeton University. Accessed August 23, 2019. http://arks.princeton.edu/ark:/88435/dsp018k71nk79v.

MLA Handbook (7^th Edition):

Yu, Fu. “Pixel-Level Prediction: From Geometry to Semantics .” 2018. Web. 23 Aug 2019.

Vancouver:

Yu F. Pixel-Level Prediction: From Geometry to Semantics . [Internet] [Doctoral dissertation]. Princeton University; 2018. [cited 2019 Aug 23]. Available from: http://arks.princeton.edu/ark:/88435/dsp018k71nk79v.

Council of Science Editors:

Yu F. Pixel-Level Prediction: From Geometry to Semantics . [Doctoral Dissertation]. Princeton University; 2018. Available from: http://arks.princeton.edu/ark:/88435/dsp018k71nk79v

NSYSU

7. Cheng, Yuan-Chen. Efficient 3D Reconstruction System for Large-scale Scene.

Degree: Master, Electrical Engineering, 2017, NSYSU

URL: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0319117-181337

► In this thesis, an efficient 3D reconstruction system is proposed to solve the problem of the huge computation of 3D reconstruction for large-scale scene. The… (more)

Subjects/Keywords: color mapping; keyframe selection; camera pose estimation; 3D reconstruction; depth cameras

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Cheng, Y. (2017). Efficient 3D Reconstruction System for Large-scale Scene. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0319117-181337

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Cheng, Yuan-Chen. “Efficient 3D Reconstruction System for Large-scale Scene.” 2017. Thesis, NSYSU. Accessed August 23, 2019. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0319117-181337.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Cheng, Yuan-Chen. “Efficient 3D Reconstruction System for Large-scale Scene.” 2017. Web. 23 Aug 2019.

Vancouver:

Cheng Y. Efficient 3D Reconstruction System for Large-scale Scene. [Internet] [Thesis]. NSYSU; 2017. [cited 2019 Aug 23]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0319117-181337.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Cheng Y. Efficient 3D Reconstruction System for Large-scale Scene. [Thesis]. NSYSU; 2017. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0319117-181337

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Johannes Gutenberg Universität Mainz

8. Gamer, Matthias. Reliability and consistency affect the integration of visual depth cues.

Degree: 2008, Johannes Gutenberg Universität Mainz

URL: http://ubm.opus.hbz-nrw.de/volltexte/2008/1742/

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Abstract Originalsprache (englisch) Visual perception relies on a two-dimensional projection of the viewed scene on the retinas of both eyes. Thus, visual depth has to… (more)

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Abstract Originalsprache (englisch) Visual perception relies on a two-dimensional projection of the viewed scene on the retinas of both eyes. Thus, visual depth has to be reconstructed from a number of different cues that are subsequently integrated to obtain robust depth percepts. Existing models of sensory integration are mainly based on the reliabilities of individual cues and disregard potential cue interactions. In the current study, an extended Bayesian model is proposed that takes into account both cue reliability and consistency. Four experiments were carried out to test this model's predictions. Observers had to judge visual displays of hemi-cylinders with an elliptical cross section, which were constructed to allow for an orthogonal variation of several competing depth cues. In Experiment 1 and 2, observers estimated the cylinder's depth as defined by shading, texture, and motion gradients. The degree of consistency among these cues was systematically varied. It turned out that the extended Bayesian model provided a better fit to the empirical data compared to the traditional model which disregards covariations among cues. To circumvent the potentially problematic assessment of single-cue reliabilities, Experiment 3 used a multiple-observation task, which allowed for estimating perceptual weights from multiple-cue stimuli. Using the same multiple-observation task, the integration of stereoscopic disparity, shading, and texture gradients was examined in Experiment 4. It turned out that less reliable cues were downweighted in the combined percept. Moreover, a specific influence of cue consistency was revealed. Shading and disparity seemed to be processed interactively while other cue combinations could be well described by additive integration rules. These results suggest that cue combination in visual depth perception is highly flexible and depends on single-cue properties as well as on interrelations among cues. The extension of the traditional cue combination model is defended in terms of the necessity for robust perception in ecologically valid environments and the current findings are discussed in the light of emerging computational theories and neuroscientific approaches.

Abstract deutsch Da die visuelle Wahrnehmung auf einer zweidimensionalen, retinalen Projektion der betrachteten Szenerie beruht, muss räumliche Tiefe aus verschiedenen Tiefenhinweisen erschlossen werden. Die Kombination dieser Merkmale führt nachfolgend zu einem stabilen Perzept. Aktuelle Modelle sensorischer Integration schreiben den Reliabilitäten einzelner Tiefenmerkmale eine prominente Rolle zu, vernachlässigen dabei jedoch deren Interaktionen untereinander. In der vorliegenden Studie wurde ein erweitertes Bayesianisches Modell erarbeitet und in vier Experimenten überprüft, das sowohl Reliabilität als auch Konsistenz verschiedener Wahrnehmungskanäle berücksichtigt. Probanden schätzten die räumliche Tiefe visuell präsentierter Halbzylinder mit elliptischer Grundfläche ein. In den Experimenten 1 und 2 wurden partiell konsistente…

Subjects/Keywords: Sensorische Integration, Tiefenkriterien; Sensory Integration, Cue Fusion, Depth Estimation; Psychology

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APA (6^th Edition):

Gamer, M. (2008). Reliability and consistency affect the integration of visual depth cues. (Doctoral Dissertation). Johannes Gutenberg Universität Mainz. Retrieved from http://ubm.opus.hbz-nrw.de/volltexte/2008/1742/

Chicago Manual of Style (16^th Edition):

Gamer, Matthias. “Reliability and consistency affect the integration of visual depth cues.” 2008. Doctoral Dissertation, Johannes Gutenberg Universität Mainz. Accessed August 23, 2019. http://ubm.opus.hbz-nrw.de/volltexte/2008/1742/.

MLA Handbook (7^th Edition):

Gamer, Matthias. “Reliability and consistency affect the integration of visual depth cues.” 2008. Web. 23 Aug 2019.

Vancouver:

Gamer M. Reliability and consistency affect the integration of visual depth cues. [Internet] [Doctoral dissertation]. Johannes Gutenberg Universität Mainz; 2008. [cited 2019 Aug 23]. Available from: http://ubm.opus.hbz-nrw.de/volltexte/2008/1742/.

Council of Science Editors:

Gamer M. Reliability and consistency affect the integration of visual depth cues. [Doctoral Dissertation]. Johannes Gutenberg Universität Mainz; 2008. Available from: http://ubm.opus.hbz-nrw.de/volltexte/2008/1742/

Georgia Tech

9. Raza, Syed H. Temporally consistent semantic segmentation in videos.

Degree: PhD, Electrical and Computer Engineering, 2014, Georgia Tech

URL: http://hdl.handle.net/1853/53455

► The objective of this Thesis research is to develop algorithms for temporally consistent semantic segmentation in videos. Though many different forms of semantic segmentations exist,… (more)

▼ The objective of this Thesis research is to develop algorithms for temporally consistent semantic segmentation in videos. Though many different forms of semantic segmentations exist, this research is focused on the problem of temporally-consistent holistic scene understanding in outdoor videos. Holistic scene understanding requires an understanding of many individual aspects of the scene including 3D layout, objects present, occlusion boundaries, and depth. Such a description of a dynamic scene would be useful for many robotic applications including object reasoning, 3D perception, video analysis, video coding, segmentation, navigation and activity recognition. Scene understanding has been studied with great success for still images. However, scene understanding in videos requires additional approaches to account for the temporal variation, dynamic information, and exploiting causality. As a first step, image-based scene understanding methods can be directly applied to individual video frames to generate a description of the scene. However, these methods do not exploit temporal information across neighboring frames. Further, lacking temporal consistency, image-based methods can result in temporally-inconsistent labels across frames. This inconsistency can impact performance, as scene labels suddenly change between frames. The objective of our this study is to develop temporally consistent scene descriptive algorithms by processing videos efficiently, exploiting causality and data-redundancy, and cater for scene dynamics. Specifically, we achieve our research objectives by (1) extracting geometric context from videos to give broad 3D structure of the scene with all objects present, (2) Detecting occlusion boundaries in videos due to depth discontinuity, (3) Estimating depth in videos by combining monocular and motion features with semantic features and occlusion boundaries. Advisors/Committee Members: Essa, Irfan (advisor), Anderson, David (advisor), Yezzi, Anthony (committee member), Barnes, Christopher (committee member), Dellaert, Frank (committee member), Sukthankar, Rahul (committee member).

Subjects/Keywords: Semantic segmentation; Temporal consistency; Causality; Videos; Occlusion boundaries; Depth estimation

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Raza, S. H. (2014). Temporally consistent semantic segmentation in videos. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/53455

Chicago Manual of Style (16^th Edition):

Raza, Syed H. “Temporally consistent semantic segmentation in videos.” 2014. Doctoral Dissertation, Georgia Tech. Accessed August 23, 2019. http://hdl.handle.net/1853/53455.

MLA Handbook (7^th Edition):

Raza, Syed H. “Temporally consistent semantic segmentation in videos.” 2014. Web. 23 Aug 2019.

Vancouver:

Raza SH. Temporally consistent semantic segmentation in videos. [Internet] [Doctoral dissertation]. Georgia Tech; 2014. [cited 2019 Aug 23]. Available from: http://hdl.handle.net/1853/53455.

Council of Science Editors:

Raza SH. Temporally consistent semantic segmentation in videos. [Doctoral Dissertation]. Georgia Tech; 2014. Available from: http://hdl.handle.net/1853/53455

10. Καπρινιώτης, Αχιλλέας. Εκτίμηση βάθους σκηνής από κάμερα τοποθετημένη σε αυτοκίνητο που κινείται.

Degree: 2014, University of Patras

URL: http://hdl.handle.net/10889/7779

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Στη διπλωματική αυτή εργασία αναλύεται η εκτίμηση του βάθους μίας άκαμπτης σκηνής από κάμερα τοποθετημένη σε αυτοκίνητο που κινείται. Στο κεφάλαιο 1 γίνεται μία εισαγωγή… (more)

▼

Στη διπλωματική αυτή εργασία αναλύεται η εκτίμηση του βάθους μίας άκαμπτης σκηνής από κάμερα τοποθετημένη σε αυτοκίνητο που κινείται. Στο κεφάλαιο 1 γίνεται μία εισαγωγή στον τομέα της Υπολογιστικής Όρασης και δίνονται μερικά παραδείγματα εφαρμογών της. Στο κεφάλαιο 2 περιγράφονται βασικές αρχές της προβολικής γεωμετρίας που χρησιμοποιείται ως μαθηματικό υπόβαθρο για τα επόμενα κεφάλαια. Στο κεφάλαιο 3 γίνεται λόγος για το θεωρητικό μοντέλο της κάμερας, των παραμέτρων της και των παραμορφώσεων που υπεισέρχονται στο μοντέλο αυτό. Στο κεφάλαιο 4 αναφέρεται η διαδικασία βαθμονόμησης της κάμερας, μαζί με την υλοποίησή της. Στο κεφάλαιο 5 παρουσιάζονται γενικές κατηγορίες των στερεοσκοπικών αλγορίθμων που χρησιμοποιούνται, καθώς και τα κατάλληλα μέτρα ομοιότητάς τους. Στο κεφάλαιο 6 γίνεται αναφορά στον ανιχνευτή γωνιών Harris και γίνεται η εφαρμογή του τόσο ως προς την ανίχνευση των γωνιών, όσο και ως προς την αντιστοίχιση των 2 εικόνων. Στο κεφάλαιο 7 αναλύεται η θεωρία του αλγόριθμου SIFT και δίνεται ένα παράδειγμα ανίχνευσης και αντιστοίχισης χαρακτηριστικών. Στο κεφάλαιο 8 επισημαίνονται οι βασικές αρχές της επιπολικής γεωμετρίας, καθώς η σημασία της διόρθωσης των εικόνων. Στο κεφάλαιο 9 αναφέρεται η συνολική διαδικασία που ακολουθήθηκε, μαζί με την περιγραφή και την υλοποίηση των μεθόδων εκτίμησης βάθους που χρησιμοποιήθηκαν.

The current master’s thesis analyzes the depth estimation of a rigid scene from a camera attached to a moving vehicle. The first chapter gives an introduction to the field of Computer Vision and provides some examples of its applications. The second chapter describes basic principles of projective geometry that are being used as mathematical background for the next chapters. The third chapter refers to the theoretical modeling of a camera, along with its parameters and the distortions that appear in this model. The forth chapter deals with the camera calibration procedure, along with its implementation. Chapter five presents general categories of stereoscopic algorithms, along with their similarity measures. Chapter six talks about Harris corner detector and its implementation in detecting corners and in the matching process as well. Chapter 7 analyzes the SIFT algorithm theory and gives an example of detecting and matching features. Chapter 8 highlights basic principles of epipolar geometry and stresses out the importance of image rectification. Chapter nine presents the procedure that has been followed, along with the description and implementation of the depth estimation methods that have been used.

Advisors/Committee Members: Δερματάς, Ευάγγελος, Kapriniotis, Achilleas, Μπερμπερίδης, Κωνσταντίνος, Ψαράκης, Εμμανουήλ.

Subjects/Keywords: Εκτίμηση βάθους; Στερεοσκοπική αντιστοίχιση; 006.37; Depth estimation; Stereo correspondence

Record Details Similar Records Cite « Share

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Καπρινιώτης, �. (2014). Εκτίμηση βάθους σκηνής από κάμερα τοποθετημένη σε αυτοκίνητο που κινείται. (Masters Thesis). University of Patras. Retrieved from http://hdl.handle.net/10889/7779

Chicago Manual of Style (16^th Edition):

Καπρινιώτης, Αχιλλέας. “Εκτίμηση βάθους σκηνής από κάμερα τοποθετημένη σε αυτοκίνητο που κινείται.” 2014. Masters Thesis, University of Patras. Accessed August 23, 2019. http://hdl.handle.net/10889/7779.

MLA Handbook (7^th Edition):

Καπρινιώτης, Αχιλλέας. “Εκτίμηση βάθους σκηνής από κάμερα τοποθετημένη σε αυτοκίνητο που κινείται.” 2014. Web. 23 Aug 2019.

Vancouver:

Καπρινιώτης �. Εκτίμηση βάθους σκηνής από κάμερα τοποθετημένη σε αυτοκίνητο που κινείται. [Internet] [Masters thesis]. University of Patras; 2014. [cited 2019 Aug 23]. Available from: http://hdl.handle.net/10889/7779.

Council of Science Editors:

Καπρινιώτης �. Εκτίμηση βάθους σκηνής από κάμερα τοποθετημένη σε αυτοκίνητο που κινείται. [Masters Thesis]. University of Patras; 2014. Available from: http://hdl.handle.net/10889/7779

Virginia Tech

11. Kotha, Bhavi Bharat. Using Texture Features To Perform Depth Estimation.

Degree: MS, Mechanical Engineering, 2018, Virginia Tech

URL: http://hdl.handle.net/10919/81895

► There is a great need in real world applications for estimating depth through electronic means without human intervention. There are many methods in the field… (more)

Subjects/Keywords: Computer Vision; Stereo Vision; Depth Estimation; Scoring; Ranking

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Kotha, B. B. (2018). Using Texture Features To Perform Depth Estimation. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/81895

Chicago Manual of Style (16^th Edition):

Kotha, Bhavi Bharat. “Using Texture Features To Perform Depth Estimation.” 2018. Masters Thesis, Virginia Tech. Accessed August 23, 2019. http://hdl.handle.net/10919/81895.

MLA Handbook (7^th Edition):

Kotha, Bhavi Bharat. “Using Texture Features To Perform Depth Estimation.” 2018. Web. 23 Aug 2019.

Vancouver:

Kotha BB. Using Texture Features To Perform Depth Estimation. [Internet] [Masters thesis]. Virginia Tech; 2018. [cited 2019 Aug 23]. Available from: http://hdl.handle.net/10919/81895.

Council of Science Editors:

Kotha BB. Using Texture Features To Perform Depth Estimation. [Masters Thesis]. Virginia Tech; 2018. Available from: http://hdl.handle.net/10919/81895

University of Houston

12. Liang, Hong 1984-. Addressing several key outstanding issues and extending the capability of the inverse scattering subseries for internal multiple attenuation, depth imaging, and parameter estimation.

Degree: Physics, Department of, 2013, University of Houston

URL: http://hdl.handle.net/10657/522

► The objective of seismic exploration is to determine the physical properties of the Earth's subsurface in order to detect potential hydrocarbon accumulations. The inverse scattering… (more)

▼ The objective of seismic exploration is to determine the physical properties of the Earth's subsurface in order to detect potential hydrocarbon accumulations. The inverse scattering series (ISS) is a multi-dimensional direct method that can perform all of the tasks associated with inversion only using the measured data and a chosen reference medium. This is achieved in stages using task-specific subseries that accomplish: (1) free-surface multiple removal; (2) internal multiple removal; (3) depth imaging; and (4) parameter estimation. This dissertation provides deeper comprehension of current ISS strengths and shortcomings for internal multiple removal, and caveats and understanding of ISS depth imaging and parameter estimation, which can be used to progress and develop further capability as part of a strategy to address the current outstanding challenges in exploration seismology. This dissertation is composed of three topics. The first topic extends the capability of the current ISS internal multiple attenuation algorithm by addressing one of its shortcomings. The current ISS internal multiple attenuator has provided added-value compared to other demultiple methods for complex media where multiple generators are not easy or able to be identified. However, this single term has its own strengths and limitations. Under certain circumstances, spurious events can be produced by the ISS leading-order attenuator. In this dissertation, higher-order terms in the ISS that address the spurious events generation from the leading-order attenuator are identified. Adding the higher-order terms to the current algorithm provides a more capable ISS internal multiple attenuation algorithm, which retains the benefit of the original algorithm and addresses the shortcoming due to spurious events. This work is part of the strategy to provide further capability for internal multiple attenuation in onshore or complex offshore exploration areas. The second project focuses on the generation and prediction of internal multiples in thin-layer models. A new method (named the reflector spectrum) based on the reflectivity forward modeling is presented to illustrate where internal multiples are generated in thin layers. The modeling of sub-resolution internal multiples leads to the concept of effective primaries. By comparing the modeling and prediction of internal multiples, it is shown that sub-resolution internal multiples cannot be predicted by the ISS internal multiple attenuator and internal multiples generated by resolvable reflectors can be accommodated by the ISS method. The third topic in the dissertation studies and evaluates the impact of matching or mismatching between the earth model type (e.g., acoustic, elastic, isotropic, anisotropic earth) that generates the data and the assumed model type behind the processing methods for ISS depth imaging and parameter estimation. Numerical results show that for ISS depth imaging and inversion applications, when the model type assumed in the processing algorithm is less complicated… Advisors/Committee Members: Weglein, Arthur B. (advisor), Francis, David J. (committee member), Hungerford, Ed (committee member), Su, Wu-Pei (committee member), Reiter, George F. (committee member).

Subjects/Keywords: Inverse scattering series; multiple attenuation; depth imaging; parameter estimation; Physics

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Liang, H. 1. (2013). Addressing several key outstanding issues and extending the capability of the inverse scattering subseries for internal multiple attenuation, depth imaging, and parameter estimation. (Thesis). University of Houston. Retrieved from http://hdl.handle.net/10657/522

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Liang, Hong 1984-. “Addressing several key outstanding issues and extending the capability of the inverse scattering subseries for internal multiple attenuation, depth imaging, and parameter estimation.” 2013. Thesis, University of Houston. Accessed August 23, 2019. http://hdl.handle.net/10657/522.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Liang, Hong 1984-. “Addressing several key outstanding issues and extending the capability of the inverse scattering subseries for internal multiple attenuation, depth imaging, and parameter estimation.” 2013. Web. 23 Aug 2019.

Vancouver:

Liang H1. Addressing several key outstanding issues and extending the capability of the inverse scattering subseries for internal multiple attenuation, depth imaging, and parameter estimation. [Internet] [Thesis]. University of Houston; 2013. [cited 2019 Aug 23]. Available from: http://hdl.handle.net/10657/522.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Liang H1. Addressing several key outstanding issues and extending the capability of the inverse scattering subseries for internal multiple attenuation, depth imaging, and parameter estimation. [Thesis]. University of Houston; 2013. Available from: http://hdl.handle.net/10657/522

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of New South Wales

13. Li, Qiang. High quality depth estimation for multi-view video.

Degree: Engineering & Information Technology, 2012, University of New South Wales

URL: http://handle.unsw.edu.au/1959.4/52142 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:10812/SOURCE01?view=true

► This thesis presents new techniques to improve the quality of adaptive structured light based depth estimation for multi-view video. By interleaving structured light with ambient… (more)

▼ This thesis presents new techniques to improve the quality of adaptive structured light based depth estimation for multi-view video. By interleaving structured light with ambient light on a frame-by-frame basis, the proposed methods can potentially capture both texture video under only ambient light for image rendering and video under both ambient light and structured light for depth estimation at video rates. By using structured light with adaptive colours which account for ambient light conditions and the colours of objects, the proposed methods not only avoid matching ambiguities in textureless areas and areas with repetitive textures but also perform robustly in areas with rich colours and textures under ambient light conditions.Firstly, a new structured light approach using adaptive colours is proposed. The adaptive colours are acquired using principal component analysis in the RGB colour space of the image of the scene under ambient light conditions. Based on a projected grid pattern of adaptive colours, a new depth estimation technique combining active and passive approaches is proposed. This technique shows the advantage of adaptive structured light over constant colours and the advantage of combining both active and passive approaches over active-only or passive-only techniques.A second new depth estimation technique using adaptive structured light and a shiftable window-based global optimization algorithm is proposed. This technique shows the advantage of adaptive structured light over random colors and generates a depth map with sharp depth discontinuities and half-pixel accuracy using the global optimization in an iterative way. A random noise pattern instead of a grid pattern is employed to improve the performance of depth estimation around object boundaries.A third new depth estimation technique using the dual-tree complex wavelet transform (DTCWT), graph cut and adaptive structured light is proposed. This technique employs the phase difference between coefficients from the DTCWT as a robust similarity measure and has the ability to keep clear depth discontinuities and detect clean and continuous occlusion areas.Finally, using the depth maps generated by the proposed techniques, image rendering is implemented through 3D warping to verify the feasibility of the proposed depth estimation techniques for multi-view video. Advisors/Committee Members: Pickering, Mark, Engineering & Information Technology, UNSW Canberra, UNSW, Frater, Michael, Engineering & Information Technology, UNSW Canberra, UNSW.

Subjects/Keywords: adaptive structured light; depth estimation; multi-view video

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Li, Q. (2012). High quality depth estimation for multi-view video. (Doctoral Dissertation). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/52142 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:10812/SOURCE01?view=true

Chicago Manual of Style (16^th Edition):

Li, Qiang. “High quality depth estimation for multi-view video.” 2012. Doctoral Dissertation, University of New South Wales. Accessed August 23, 2019. http://handle.unsw.edu.au/1959.4/52142 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:10812/SOURCE01?view=true.

MLA Handbook (7^th Edition):

Li, Qiang. “High quality depth estimation for multi-view video.” 2012. Web. 23 Aug 2019.

Vancouver:

Li Q. High quality depth estimation for multi-view video. [Internet] [Doctoral dissertation]. University of New South Wales; 2012. [cited 2019 Aug 23]. Available from: http://handle.unsw.edu.au/1959.4/52142 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:10812/SOURCE01?view=true.

Council of Science Editors:

Li Q. High quality depth estimation for multi-view video. [Doctoral Dissertation]. University of New South Wales; 2012. Available from: http://handle.unsw.edu.au/1959.4/52142 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:10812/SOURCE01?view=true

University of Delaware

14. Guo, Xinqing. Combining learning and computational imaging for 3D inference .

Degree: 2017, University of Delaware

URL: http://udspace.udel.edu/handle/19716/23209

► Acquiring 3D geometry of the scene is a key task in computer vision. Applications are numerous, from classical object reconstruction and scene understanding to the… (more)

▼ Acquiring 3D geometry of the scene is a key task in computer vision. Applications are numerous, from classical object reconstruction and scene understanding to the more recent visual SLAM and autonomous driving. Recent advances in computational imaging have enabled many new solutions to tackle the problem of 3D reconstruction. By modifying the camera's components, computational imaging optically encodes the scene, then decodes it with tailored algorithms. ☐ This dissertation focuses on exploring new computational imaging techniques, combined with recent advances in deep learning, to infer 3D geometry of the scene. In general, our approaches can be categorized into active and passive 3D sensing. ☐ For active illumination methods, we propose two solutions: first, we present a multi-flash (MF) system implemented on the mobile platform. Using the sequence of images captured by the MF system, we can extract the depth edges of the scene, and further estimate a depth map on a mobile device. Next, we show a portable immersive system that is capable of acquiring and displaying high fidelity 3D reconstructions using a set of RGB-D sensors. The system is based on structured light technique and is able to recover 3D geometry of the scene in real time. We have also developed a visualization system that allows users to dynamically visualize the event from new perspectives at arbitrary time instances in real time. ☐ For passive sensing methods, we focus on light field based depth estimation. For depth inference from a single light field, we present an algorithm that is tailored for barcode images. Our algorithm analyzes the statistics of raw light field images and conducts depth estimation with real time speed for fast refocusing and decoding. To mimic the human vision system, we investigate the dual light field input and propose a unified deep learning based framework to extract depth from both disparity cue and focus cue. To facilitate training, we have created a large dual focal stack database with ground truth disparity. While above solution focuses on fusing depth from focus and stereo, we also exploit combing depth from defocus and stereo, with an all-focus stereo pair and a defocused image of one of the stereo views as input. We have adopted the hourglass network architecture to extract depth from the image triplets. We have then studied and explored multiple neural network architectures to improve depth inference. We demonstrate that our deep learning based approaches preserve the strength of focus/defocus cue and disparity cue while effectively suppressing their weaknesses.

Subjects/Keywords: Applied sciences; Computational imaging; Deep learning; Depth estimation; Light field

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Guo, X. (2017). Combining learning and computational imaging for 3D inference . (Doctoral Dissertation). University of Delaware. Retrieved from http://udspace.udel.edu/handle/19716/23209

Chicago Manual of Style (16^th Edition):

Guo, Xinqing. “Combining learning and computational imaging for 3D inference .” 2017. Doctoral Dissertation, University of Delaware. Accessed August 23, 2019. http://udspace.udel.edu/handle/19716/23209.

MLA Handbook (7^th Edition):

Guo, Xinqing. “Combining learning and computational imaging for 3D inference .” 2017. Web. 23 Aug 2019.

Vancouver:

Guo X. Combining learning and computational imaging for 3D inference . [Internet] [Doctoral dissertation]. University of Delaware; 2017. [cited 2019 Aug 23]. Available from: http://udspace.udel.edu/handle/19716/23209.

Council of Science Editors:

Guo X. Combining learning and computational imaging for 3D inference . [Doctoral Dissertation]. University of Delaware; 2017. Available from: http://udspace.udel.edu/handle/19716/23209

KTH

15. Nassir, Cesar. Domain-Independent Moving Object Depth Estimation using Monocular Camera.

Degree: RPL, 2018, KTH

URL: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-233519

►

Today automotive companies across the world strive to create vehicles with fully autonomous capabilities. There are many benefits of developing autonomous vehicles, such as… (more)

▼

Today automotive companies across the world strive to create vehicles with fully autonomous capabilities. There are many benefits of developing autonomous vehicles, such as reduced traffic congestion, increased safety and reduced pollution, etc. To be able to achieve that goal there are many challenges ahead, one of them is visual perception. Being able to estimate depth from a 2D image has been shown to be a key component for 3D recognition, reconstruction and segmentation. Being able to estimate depth in an image from a monocular camera is an ill-posed problem since there is ambiguity between the mapping from colour intensity and depth value. Depth estimation from stereo images has come far compared to monocular depth estimation and was initially what depth estimation relied on. However, being able to exploit monocular cues is necessary for scenarios when stereo depth estimation is not possible. We have presented a novel CNN network, BiNet which is inspired by ENet, to tackle depth estimation of moving objects using only a monocular camera in real-time. It performs better than ENet in the Cityscapes dataset while adding only a small overhead to the complexity.

I dag strävar bilföretag över hela världen för att skapa fordon med helt autonoma möjligheter. Det finns många fördelar med att utveckla autonoma fordon, såsom minskad trafikstockning, ökad säkerhet och minskad förorening, etc. För att kunna uppnå det målet finns det många utmaningar framåt, en av dem är visuell uppfattning. Att kunna uppskatta djupet från en 2D-bild har visat sig vara en nyckelkomponent för 3D-igenkännande, rekonstruktion och segmentering. Att kunna uppskatta djupet i en bild från en monokulär kamera är ett svårt problem eftersom det finns tvetydighet mellan kartläggningen från färgintensitet och djupvärde. Djupestimering från stereobilder har kommit långt jämfört med monokulär djupestimering och var ursprungligen den metod som man har förlitat sig på. Att kunna utnyttja monokulära bilder är dock nödvändig för scenarier när stereodjupuppskattning inte är möjligt. Vi har presenterat ett nytt nätverk, BiNet som är inspirerat av ENet, för att ta itu med djupestimering av rörliga objekt med endast en monokulär kamera i realtid. Det fungerar bättre än ENet med datasetet Cityscapes och lägger bara till en liten kostnad på komplexiteten.

Subjects/Keywords: Robotics; Deep Learning; Computer Vision; Depth Estimation; Robotics; Robotteknik och automation

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Nassir, C. (2018). Domain-Independent Moving Object Depth Estimation using Monocular Camera. (Thesis). KTH. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-233519

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Nassir, Cesar. “Domain-Independent Moving Object Depth Estimation using Monocular Camera.” 2018. Thesis, KTH. Accessed August 23, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-233519.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Nassir, Cesar. “Domain-Independent Moving Object Depth Estimation using Monocular Camera.” 2018. Web. 23 Aug 2019.

Vancouver:

Nassir C. Domain-Independent Moving Object Depth Estimation using Monocular Camera. [Internet] [Thesis]. KTH; 2018. [cited 2019 Aug 23]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-233519.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Nassir C. Domain-Independent Moving Object Depth Estimation using Monocular Camera. [Thesis]. KTH; 2018. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-233519

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Sydney

16. Fu, Huan. Robust Dense Prediction for Visual Perception .

Degree: 2019, University of Sydney

URL: http://hdl.handle.net/2123/20123

► Dense prediction or pixel-level labeling targets at predicting labels of interest (e.g., categories, depth values, flow vectors, and edge probabilities) for each pixel of an… (more)

▼ Dense prediction or pixel-level labeling targets at predicting labels of interest (e.g., categories, depth values, flow vectors, and edge probabilities) for each pixel of an input image. This middle-level computer vision problem plays a crucial role in establishing visual perception systems for the future intelligent world. Therefore, tremendous efforts have been made in the past decades to explore the solution for robust dense prediction, and recent studies have continuously obtained significant progress relying on deep Fully Convolutional Networks (FCNs). According to the expected label, dense prediction contains a set of subtasks. Building robust models for each task must examine the particular property, but the main intuition and motivation for the network architecture development are shared across different tasks. In the thesis, we take the well-known problems of scene parsing, monocular depth estimation, and edge detection as examples, and devise some advanced and highly extensible techniques by addressing both the individual and collective issues for robust dense prediction. Specific to scene parsing, employing hierarchical convolutional features is essential to obtain high-resolution and fine-grained predictions. Previous algorithms regularly aggregate them via concatenation or linear combination, which cannot sufficiently exploit the diversities of the contextual information and the spatial inhomogeneity of a scene. We propose some novel attention mechanisms, i.e., adaptive hierarchical feature aggregation (AHFA) and mixture-of-experts (MoE), to re-weight different levels of features at each spatial location according to the local structure and surrounding contextual information before aggregation. Existing works on depth estimation often overlook the strong inherent ordinal correlation of depth values resulting in inferior performance. Motivated by the observation, we introduce the ranking mechanism for depth estimation by proposing an effective ordinal regression constraint. For edge detection, common approaches simply predict the boundary probability for each pixel individually from the receptive fields where the pixel is centered at. Differently, we propose that modeling the boundary structures or position sensitive scores are more flexible because of the implied feature competition for the prediction of each spatial position. We also study unsupervised domain mapping which is of general applicability, enabling a consolidated solution for dense prediction. Advanced unsupervised domain mapping approaches mainly rely on Generative Adversarial Networks (GANs) to make the prediction indistinguishable from reality (e.g., generated pseudo parsing vs. truth parsing), and reduce the solution space with high-level constraints and assumptions to guarantee that an input and the corresponding output are paired up in a meaningful way in the absence of unmatched training samples. However, they overlook the special property of images that simple geometric transformations do not change the semantics of an image.…

Subjects/Keywords: dense prediction; domain mapping; scene parsing; GANs; depth estimation; boundary detection

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Fu, H. (2019). Robust Dense Prediction for Visual Perception . (Thesis). University of Sydney. Retrieved from http://hdl.handle.net/2123/20123

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Fu, Huan. “Robust Dense Prediction for Visual Perception .” 2019. Thesis, University of Sydney. Accessed August 23, 2019. http://hdl.handle.net/2123/20123.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Fu, Huan. “Robust Dense Prediction for Visual Perception .” 2019. Web. 23 Aug 2019.

Vancouver:

Fu H. Robust Dense Prediction for Visual Perception . [Internet] [Thesis]. University of Sydney; 2019. [cited 2019 Aug 23]. Available from: http://hdl.handle.net/2123/20123.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Fu H. Robust Dense Prediction for Visual Perception . [Thesis]. University of Sydney; 2019. Available from: http://hdl.handle.net/2123/20123

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

17. Stransky, Debi. First and Second Order Stereoscopic Processing of Fused and Diplopic Targets.

Degree: PhD, Psychology (Functional Area: Brain, Behaviour & Cognitive Science, 2015, York University

URL: http://hdl.handle.net/10315/29941

► Depth from stereopsis is due to the positional difference between the two eyes, which results in each eye receiving a different view of the world.… (more)

▼ Depth from stereopsis is due to the positional difference between the two eyes, which results in each eye receiving a different view of the world. Although progress has been made in understanding how the visual system processes stereoscopic stimuli, a number of questions remain. The goal of this work was to assess the relationship between the perceptual, the temporal and the 1st- /2nd- order dichotomies of stereopsis and in doing so, determine an appropriate method for measuring depth from large disparities. To this end, stereosensitivity and perceived depth were assessed using 1st- and 2nd- order stimuli over a range of test disparities and conditions. The main contributions of this research are as follows: 1) The sustained/transient dichotomy proposed by Edwards, Pope and Schor (2000) is best considered in terms of the spatial dichotomy proposed by Hess and Wilcox (1994). At large disparities it is not possible to categorize performance based on exposure duration alone; 2) There is not a simple correspondence between Ogle's (1952) patent / qualitative perceptual categories and the 1st- /2nd- order dichotomy proposed by Hess and Wilcox (1994); 3) Quantitative depth is provided by both 1st- and 2nd- order mechanisms in the fused range, but only the 2nd- order signal is used when stimuli are diplopic; 3) The quantitative depth provided by a 2nd- order stimulus scales with envelope size; and 4) The monoptic depth phenomenon may be related to depth from diplopic stimuli, but for conditions tested here when both monoptic depth and 2nd- order stereopsis are available, the latter is used to encode depth percepts. The results reported here expand on earlier work on 1st- and 2nd- order stereopsis and address the issues in the methodologies used to study depth from large disparities. These results are consistent with the widely accepted filter-rectify-filter model of 2nd- order processing, and 1st- and 2nd- order stimuli are likely encoded by disparity-sensitive neurons via a two-stream model (see Wilson, Ferrera, and Yo (1992); Zhou and Baker (1993)). Advisors/Committee Members: Wilcox, Laurie M. (advisor).

Subjects/Keywords: Experimental psychology; Psychology; Neurosciences; Stereopsis; Stereoscopic 3D; 1st- order; 2nd- order; Non-linear mechanism; Fused; Fusion; Diplopic; Diplopia; Depth; Disparity; Metric depth; Depth estimation; Stereoacuity; Stereosensitivity; Spatial dichotomy; Monoptic depth

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Stransky, D. (2015). First and Second Order Stereoscopic Processing of Fused and Diplopic Targets. (Doctoral Dissertation). York University. Retrieved from http://hdl.handle.net/10315/29941

Chicago Manual of Style (16^th Edition):

Stransky, Debi. “First and Second Order Stereoscopic Processing of Fused and Diplopic Targets.” 2015. Doctoral Dissertation, York University. Accessed August 23, 2019. http://hdl.handle.net/10315/29941.

MLA Handbook (7^th Edition):

Stransky, Debi. “First and Second Order Stereoscopic Processing of Fused and Diplopic Targets.” 2015. Web. 23 Aug 2019.

Vancouver:

Stransky D. First and Second Order Stereoscopic Processing of Fused and Diplopic Targets. [Internet] [Doctoral dissertation]. York University; 2015. [cited 2019 Aug 23]. Available from: http://hdl.handle.net/10315/29941.

Council of Science Editors:

Stransky D. First and Second Order Stereoscopic Processing of Fused and Diplopic Targets. [Doctoral Dissertation]. York University; 2015. Available from: http://hdl.handle.net/10315/29941

University of California – San Diego

18. Liu, Lee-Kang. From Image to Video, Depth Data Reconstruction from a Subset of Samples: Representations, Algorithms, and Sampling Strategies.

Degree: Electrical Engineering (Signal and Image Proc), 2015, University of California – San Diego

URL: http://www.escholarship.org/uc/item/98f001p4

► Depth data acquisition has drawn considerable interest in recent years as a result of the rapid development of 3D technology. A large number of acquisition… (more)

▼ Depth data acquisition has drawn considerable interest in recent years as a result of the rapid development of 3D technology. A large number of acquisition techniques are based on hardware devices, e.g., infra-red sensors, time-of-flight camera, and LiDAR, etc, whereas they have limited performance due to poor depth precision and low resolution. In some situations computational methods are preferred due to its flexibility and low cost. These computational techniques, typically known as depth estimation algorithms, estimate depth maps (in terms of disparities) from a pair of stereo images. However, existing computational techniques are sensitive to various factors such as noise, camera alignment, and illumination, resulting that a few samples are reliable. Therefore, dense depth data reconstruction from sparse samples is a significant technological challenge.In this thesis, we mainly consider the problem of dense depth data reconstruction from a subset of samples. We present computationally efficient methods to estimate dense depth maps from sparse measurements, and we further extend the work to dense depth video estimation. Working on single depth image, we have three main contributions: First, we provide empirical evidence that depth maps can be encoded much more sparsely than natural images by using common dictionaries such as wavelets and contourlets, and show that disparity maps can be sparsely represented by a combined wavelet and contourlet dictionary. Second, we propose a subgradient algorithm for dense depth image reconstruction, and propose an alternating direction methods of multipliers (ADMM) algorithm with a multi-scale warm start procedure to further speed up the convergence. Third, we propose a two-stage randomized sampling scheme to optimally choose the sampling locations, thus maximizing the reconstruction performance for a given sampling budget. Experimental results show that the proposed methods produce high quality dense depth estimates, and are robust to noisy measurements.For dealing with depth video sequences, a framework for depth video reconstruction from a subset of samples is proposed. By redefining classical dense depth estimation into two individual problems, sensing and synthesis, we propose a motion compensation assisted sampling (MCAS) scheme and a spatio-temporal depth reconstruction (STDR) algorithm for reconstructing depth video sequences from a subset of samples. Using the 3-dimensional extensible dictionary, 3D-DWT, and applying alternating direction method of multiplier technique, the proposed STDR algorithm possesses scability for temporal volume and efficiency for processing large scale depth data. Exploiting the temporal information and corresponding RGB images, the proposed MCAS scheme achieves an efficient 1-Stage sampling. Experimental results show that the proposed depth reconstruction framework outperforms the existing methods and is competitive comparing to our previous work on sampling single depth image, which requires a pilot signal in the 2-Stage sampling scheme.…

Subjects/Keywords: Engineering; Alternating Direction Method of Multipliers; Dense Depth Estimation; Depth Enhancement; Image and Video Processing; Sparse Reconstruction

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Liu, L. (2015). From Image to Video, Depth Data Reconstruction from a Subset of Samples: Representations, Algorithms, and Sampling Strategies. (Thesis). University of California – San Diego. Retrieved from http://www.escholarship.org/uc/item/98f001p4

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Liu, Lee-Kang. “From Image to Video, Depth Data Reconstruction from a Subset of Samples: Representations, Algorithms, and Sampling Strategies.” 2015. Thesis, University of California – San Diego. Accessed August 23, 2019. http://www.escholarship.org/uc/item/98f001p4.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Liu, Lee-Kang. “From Image to Video, Depth Data Reconstruction from a Subset of Samples: Representations, Algorithms, and Sampling Strategies.” 2015. Web. 23 Aug 2019.

Vancouver:

Liu L. From Image to Video, Depth Data Reconstruction from a Subset of Samples: Representations, Algorithms, and Sampling Strategies. [Internet] [Thesis]. University of California – San Diego; 2015. [cited 2019 Aug 23]. Available from: http://www.escholarship.org/uc/item/98f001p4.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Liu L. From Image to Video, Depth Data Reconstruction from a Subset of Samples: Representations, Algorithms, and Sampling Strategies. [Thesis]. University of California – San Diego; 2015. Available from: http://www.escholarship.org/uc/item/98f001p4

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

EPFL

19. Akin, Abdulkadir. Real-Time High-Resolution Multiple-Camera Depth Map Estimation Hardware and Its Applications.

Degree: 2015, EPFL

URL: http://infoscience.epfl.ch/record/207024

► Depth information is used in a variety of 3D based signal processing applications such as autonomous navigation of robots and driving systems, object detection and… (more)

▼ Depth information is used in a variety of 3D based signal processing applications such as autonomous navigation of robots and driving systems, object detection and tracking, computer games, 3D television, and free view-point synthesis. These applications require high accuracy and speed performances for depth estimation. Depth maps can be generated using disparity estimation methods, which are obtained from stereo matching between multiple images. The computational complexity of disparity estimation algorithms and the need of large size and bandwidth for the external and internal memory make the real-time processing of disparity estimation challenging, especially for high resolution images. This thesis proposes a high-resolution high-quality multiple-camera depth map estimation hardware. The proposed hardware is verified in real-time with a complete system from the initial image capture to the display and applications. The details of the complete system are presented. The proposed binocular and trinocular adaptive window size disparity estimation algorithms are carefully designed to be suitable to real-time hardware implementation by allowing efficient parallel and local processing while providing high-quality results. The proposed binocular and trinocular disparity estimation hardware implementations can process 55 frames per second on a Virtex-7 FPGA at a 1024 x 768 XGA video resolution for a 128 pixel disparity range. The proposed binocular disparity estimation hardware provides best quality compared to existing real-time high-resolution disparity estimation hardware implementations. A novel compressed-look up table based rectification algorithm and its real-time hardware implementation are presented. The low-complexity decompression process of the rectification hardware utilizes a negligible amount of LUT and DFF resources of the FPGA while it does not require the existence of external memory. The first real-time high-resolution free viewpoint synthesis hardware utilizing three-camera disparity estimation is presented. The proposed hardware generates high-quality free viewpoint video in real-time for any horizontally aligned arbitrary camera positioned between the leftmost and rightmost physical cameras. The full embedded system of the depth estimation is explained. The presented embedded system transfers disparity results together with synchronized RGB pixels to the PC for application development. Several real-time applications are developed on a PC using the obtained RGB+D results. The implemented depth estimation based real-time software applications are: depth based image thresholding, speed and distance measurement, head-hands-shoulders tracking, virtual mouse using hand tracking and face tracking integrated with free viewpoint synthesis. The proposed binocular disparity estimation hardware is implemented in an ASIC. The ASIC implementation of disparity estimation imposes additional constraints with respect to the FPGA implementation. These restrictions, their implemented efficient solutions and the ASIC… Advisors/Committee Members: Leblebici, Yusuf, Schmid, Alexandre.

Subjects/Keywords: Depth Estimation; Disparity Estimation; Rectification; Free Viewpoint Synthesis; Multiple Camera; Hardware Implementation; Real-Time; FPGA; ASIC

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Akin, A. (2015). Real-Time High-Resolution Multiple-Camera Depth Map Estimation Hardware and Its Applications. (Thesis). EPFL. Retrieved from http://infoscience.epfl.ch/record/207024

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Akin, Abdulkadir. “Real-Time High-Resolution Multiple-Camera Depth Map Estimation Hardware and Its Applications.” 2015. Thesis, EPFL. Accessed August 23, 2019. http://infoscience.epfl.ch/record/207024.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Akin, Abdulkadir. “Real-Time High-Resolution Multiple-Camera Depth Map Estimation Hardware and Its Applications.” 2015. Web. 23 Aug 2019.

Vancouver:

Akin A. Real-Time High-Resolution Multiple-Camera Depth Map Estimation Hardware and Its Applications. [Internet] [Thesis]. EPFL; 2015. [cited 2019 Aug 23]. Available from: http://infoscience.epfl.ch/record/207024.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Akin A. Real-Time High-Resolution Multiple-Camera Depth Map Estimation Hardware and Its Applications. [Thesis]. EPFL; 2015. Available from: http://infoscience.epfl.ch/record/207024

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

20. Mollén, Katarina. Water Depth Estimation Using Ultrasound Pulses for Handheld Diving Equipment.

Degree: The Institute of Technology, 2015, Linköping UniversityLinköping University

URL: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-117061

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This thesis studies the design and implementation of an ultra-sonic water depth sounder. The depth sounder is implemented in a hand-held smart console used… (more)

▼

This thesis studies the design and implementation of an ultra-sonic water depth sounder. The depth sounder is implemented in a hand-held smart console used by divers. Since the idea of echo sounding is to measure the flight time between transmitting the signal and receiving the echo, the main challenge of this task is to find a time-of-flight (ToF) estimation for a signal in noise. It should be suitable for this specific application and robust when implemented in the device. The thesis contains an investigation of suitable ToF methods. More detailed evaluations of the matched filter, also known as the correlation method, and the linear phase approach are done. Aspects like pulse frequency and duration, speed of sound in water and underwater noise are taken into account. The ToF-methods are evaluated through simulation and experiments. The matched filter approach is found suitable based on these simulations and tests with signals recorded by the console. This verification leads to the implementation of the algorithm on the device. The algorithm is tested in real time, the results are evaluated and improvements suggested.

Denna rapport behandlar skattning av vattendjup med hjälp av ultraljudspulser och implementation av detta. Djupmätaren implementeras i en handhållen dykarkonsoll. Eftersom grundidén i ekolodning är att mäta tiden mellan att pulsen skickas iväg och att ekot tas emot är en stor del av utmaningen att hitta en lämplig metod för att skatta flykttiden för en signal i brus. Metoden ska passa för detta användingsområde och vara robust. Rapporten tar upp tidigare forskning gjord inom flykttidsestimering. De metoder som utvärderas för implementation är det matchade filtret, också kallad korrelationsmetoden, och linjär fas-metoden. Andra aspekter som avvägs och utreds är pulsfrekvens och pulsvaraktighet, ljudets hastighet och brus under vattnet. Metoderna för att skatta flykttid utvärderas genom simuleringar. Det matchade filtret bedöms vara lämpligt baserat på dessa simuleringar och experiment med data inspelad med konsollen. Denna verifikation leder till att algoritmen implementeras på konsollen. Den implementerade algoritmen testas i realtid, resultaten utvärderas och förbättringar föreslås.

Subjects/Keywords: Depth sounding; Echo sounding; Underwater ultrasounding; Time of flight estimation; Time delay estimation; Matched filter; Cross correlation; GCC; PHAT; ML

4 more images…

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APA (6^th Edition):

Mollén, K. (2015). Water Depth Estimation Using Ultrasound Pulses for Handheld Diving Equipment. (Thesis). Linköping UniversityLinköping University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-117061

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Mollén, Katarina. “Water Depth Estimation Using Ultrasound Pulses for Handheld Diving Equipment.” 2015. Thesis, Linköping UniversityLinköping University. Accessed August 23, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-117061.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Mollén, Katarina. “Water Depth Estimation Using Ultrasound Pulses for Handheld Diving Equipment.” 2015. Web. 23 Aug 2019.

Vancouver:

Mollén K. Water Depth Estimation Using Ultrasound Pulses for Handheld Diving Equipment. [Internet] [Thesis]. Linköping UniversityLinköping University; 2015. [cited 2019 Aug 23]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-117061.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Mollén K. Water Depth Estimation Using Ultrasound Pulses for Handheld Diving Equipment. [Thesis]. Linköping UniversityLinköping University; 2015. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-117061

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Johannes Gutenberg Universität Mainz

21. Frech, Birte. Verhaltensphysiologische Analyse der visuellen Wahrnehmung räumlicher Tiefe beim Goldfisch.

Degree: 2009, Johannes Gutenberg Universität Mainz

URL: http://ubm.opus.hbz-nrw.de/volltexte/2009/2116/

►

Die Frage, wie es zur visuellen Wahrnehmung räumlicher Tiefe kommt, wenn das Retinabild nur zweidimensional ist, gehört zu den grundlegenden Proble-men der Hirnforschung. Für Tiere,… (more)

▼

Die Frage, wie es zur visuellen Wahrnehmung räumlicher Tiefe kommt, wenn das Retinabild nur zweidimensional ist, gehört zu den grundlegenden Proble-men der Hirnforschung. Für Tiere, die sich aktiv in ihrer Umgebung bewegen, herrscht ein großer Selektionsdruck Entfernungen und Größen richtig einzu-schätzen. Ziel der vorliegenden Arbeit war es, herauszufinden, ob und wie gut Goldfische Objekte allein aufgrund des Abstandes unterscheiden können und woraus sie Information über den Abstand gewinnen. Hierzu wurde ein Ver-suchsaufbau mit homogen weißem Hintergrund entworfen, in dem die Akkom-modation als Entfernungsinformationen verwendet werden kann, weniger je-doch die Bewegungsparallaxe. Die Goldfische lernten durch operante Konditio-nierung einen Stimulus (schwarze Kreisscheibe) in einem bestimmten Abstand zu wählen, während ein anderer, gleichgroßer Stimulus so entfernt wie möglich präsentiert wurde. Der Abstand zwischen den Stimuli wurde dann verringert, bis die Goldfische keine sichere Wahl für den Dressurstimulus mehr treffen konnten. Die Unterscheidungsleistung der Goldfische wurde mit zunehmendem Abstand des Dressurstimulus immer geringer. Eine Wiederholung der Versuche mit unscharfen Stimu¬lus¬kon¬turen brachte keine Verschlechterung in der Unter-scheidung, was Akkommodation wenig wahrscheinlich macht. Um die Größen-konstanz beim Goldfisch zu testen, wurden die Durchmesser der unterschiedlich entfernten Stimuli so angepasst, dass sie für den Goldfisch die gleiche Retina-bildgröße hatten. Unter diesen Bedingungen waren die Goldfische nicht in der Lage verschieden entfernte Stimuli zu unterscheiden und somit Größenkonstanz zu leisten. Es fand demnach keine echte Entfernungsbestimmung oder Tiefen-wahrneh¬mung statt. Die Unterscheidung der verschieden entfernten Stimuli erfolgte allein durch deren Abbildungsgröße auf der Retina. Dass die Goldfische bei diesem Experiment nicht akkommodieren, wurde durch Infrarot-Photoretinoskopie gezeigt. Somit lässt sich Akkommodation für die Entfer-nungsbestimmung in diesen Versuchen ausschließen. Für diese Leistung und die Größenkonstanz ist vermutlich die Bewegungsparallaxe entscheidend.

The question, how the visual perception of spatial depth is possible with a two dimensional retinal image, is one of the fundamental problems in brain research. There is a high selection pressure for active moving animals to judge distances and sizes correctly. The purpose of this thesis was to find out how good goldfish are in discriminating objects only by distance and which information they may use. A setup with a homogenous white sur-rounding was designed to limit visual depth cues mainly to accommodation and less to motion parallax. Goldfish were trained by operant conditioning to choose one stimulus in a defined distance, while another equally sized stimulus was presented a far as possible from the first one. The distance between the stimuli was decreased until the goldfish could no longer tell them apart. The discrimination ability of the goldfish of two similar sized stimuli in…

Subjects/Keywords: Sehen, Entfernungswahrnehmung, Goldfisch, operante Kondtionierung; depth perception, distance estimation, vision, goldfish, operant conditioning; Life sciences

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Frech, B. (2009). Verhaltensphysiologische Analyse der visuellen Wahrnehmung räumlicher Tiefe beim Goldfisch. (Doctoral Dissertation). Johannes Gutenberg Universität Mainz. Retrieved from http://ubm.opus.hbz-nrw.de/volltexte/2009/2116/

Chicago Manual of Style (16^th Edition):

Frech, Birte. “Verhaltensphysiologische Analyse der visuellen Wahrnehmung räumlicher Tiefe beim Goldfisch.” 2009. Doctoral Dissertation, Johannes Gutenberg Universität Mainz. Accessed August 23, 2019. http://ubm.opus.hbz-nrw.de/volltexte/2009/2116/.

MLA Handbook (7^th Edition):

Frech, Birte. “Verhaltensphysiologische Analyse der visuellen Wahrnehmung räumlicher Tiefe beim Goldfisch.” 2009. Web. 23 Aug 2019.

Vancouver:

Frech B. Verhaltensphysiologische Analyse der visuellen Wahrnehmung räumlicher Tiefe beim Goldfisch. [Internet] [Doctoral dissertation]. Johannes Gutenberg Universität Mainz; 2009. [cited 2019 Aug 23]. Available from: http://ubm.opus.hbz-nrw.de/volltexte/2009/2116/.

Council of Science Editors:

Frech B. Verhaltensphysiologische Analyse der visuellen Wahrnehmung räumlicher Tiefe beim Goldfisch. [Doctoral Dissertation]. Johannes Gutenberg Universität Mainz; 2009. Available from: http://ubm.opus.hbz-nrw.de/volltexte/2009/2116/

Brunel University

22. Alazawi, Eman. Holoscopic 3D image depth estimation and segmentation techniques.

Degree: PhD, 2015, Brunel University

URL: http://bura.brunel.ac.uk/handle/2438/10517 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.642452

► Today’s 3D imaging techniques offer significant benefits over conventional 2D imaging techniques. The presence of natural depth information in the scene affords the observer an… (more)

▼ Today’s 3D imaging techniques offer significant benefits over conventional 2D imaging techniques. The presence of natural depth information in the scene affords the observer an overall improved sense of reality and naturalness. A variety of systems attempting to reach this goal have been designed by many independent research groups, such as stereoscopic and auto-stereoscopic systems. Though the images displayed by such systems tend to cause eye strain, fatigue and headaches after prolonged viewing as users are required to focus on the screen plane/accommodation to converge their eyes to a point in space in a different plane/convergence. Holoscopy is a 3D technology that targets overcoming the above limitations of current 3D technology and was recently developed at Brunel University. This work is part W4.1 of the 3D VIVANT project that is funded by the EU under the ICT program and coordinated by Dr. Aman Aggoun at Brunel University, West London, UK. The objective of the work described in this thesis is to develop estimation and segmentation techniques that are capable of estimating precise 3D depth, and are applicable for holoscopic 3D imaging system. Particular emphasis is given to the task of automatic techniques i.e. favours algorithms with broad generalisation abilities, as no constraints are placed on the setting. Algorithms that provide invariance to most appearance based variation of objects in the scene (e.g. viewpoint changes, deformable objects, presence of noise and changes in lighting). Moreover, have the ability to estimate depth information from both types of holoscopic 3D images i.e. Unidirectional and Omni-directional which gives horizontal parallax and full parallax (vertical and horizontal), respectively. The main aim of this research is to develop 3D depth estimation and 3D image segmentation techniques with great precision. In particular, emphasis on automation of thresholding techniques and cues identifications for development of robust algorithms. A method for depth-through-disparity feature analysis has been built based on the existing correlation between the pixels at a one micro-lens pitch which has been exploited to extract the viewpoint images (VPIs). The corresponding displacement among the VPIs has been exploited to estimate the depth information map via setting and extracting reliable sets of local features. ii Feature-based-point and feature-based-edge are two novel automatic thresholding techniques for detecting and extracting features that have been used in this approach. These techniques offer a solution to the problem of setting and extracting reliable features automatically to improve the performance of the depth estimation related to the generalizations, speed and quality. Due to the resolution limitation of the extracted VPIs, obtaining an accurate 3D depth map is challenging. Therefore, sub-pixel shift and integration is a novel interpolation technique that has been used in this approach to generate super-resolution VPIs. By shift and integration of a set of up-sampled low…

Subjects/Keywords: 621.36; Holoscopic 3D image; Depth map estimation; Segmentation; Super resolution image; Subjective evaluation

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Alazawi, E. (2015). Holoscopic 3D image depth estimation and segmentation techniques. (Doctoral Dissertation). Brunel University. Retrieved from http://bura.brunel.ac.uk/handle/2438/10517 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.642452

Chicago Manual of Style (16^th Edition):

Alazawi, Eman. “Holoscopic 3D image depth estimation and segmentation techniques.” 2015. Doctoral Dissertation, Brunel University. Accessed August 23, 2019. http://bura.brunel.ac.uk/handle/2438/10517 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.642452.

MLA Handbook (7^th Edition):

Alazawi, Eman. “Holoscopic 3D image depth estimation and segmentation techniques.” 2015. Web. 23 Aug 2019.

Vancouver:

Alazawi E. Holoscopic 3D image depth estimation and segmentation techniques. [Internet] [Doctoral dissertation]. Brunel University; 2015. [cited 2019 Aug 23]. Available from: http://bura.brunel.ac.uk/handle/2438/10517 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.642452.

Council of Science Editors:

Alazawi E. Holoscopic 3D image depth estimation and segmentation techniques. [Doctoral Dissertation]. Brunel University; 2015. Available from: http://bura.brunel.ac.uk/handle/2438/10517 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.642452

Louisiana State University

23. Maier, Christopher Allan. Palate shape and depth : a shape matching and machine learning method for assessment of ancestry from skeletal remains.

Degree: MA, Social and Behavioral Sciences, 2013, Louisiana State University

URL: etd-03182013-190045 ; https://digitalcommons.lsu.edu/gradschool_theses/1540

► The assessment of ancestry from skeletal remains is a vital aspect of forensic anthropology. As such, a myriad of techniques exists for estimating this particular… (more)

Subjects/Keywords: Skeletal Ancestry; Forensic Anthropology; Ancestry Estimation; Palate Depth; Palate Shape; Shape Matching; Machine Learning

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Maier, C. A. (2013). Palate shape and depth : a shape matching and machine learning method for assessment of ancestry from skeletal remains. (Masters Thesis). Louisiana State University. Retrieved from etd-03182013-190045 ; https://digitalcommons.lsu.edu/gradschool_theses/1540

Chicago Manual of Style (16^th Edition):

Maier, Christopher Allan. “Palate shape and depth : a shape matching and machine learning method for assessment of ancestry from skeletal remains.” 2013. Masters Thesis, Louisiana State University. Accessed August 23, 2019. etd-03182013-190045 ; https://digitalcommons.lsu.edu/gradschool_theses/1540.

MLA Handbook (7^th Edition):

Maier, Christopher Allan. “Palate shape and depth : a shape matching and machine learning method for assessment of ancestry from skeletal remains.” 2013. Web. 23 Aug 2019.

Vancouver:

Maier CA. Palate shape and depth : a shape matching and machine learning method for assessment of ancestry from skeletal remains. [Internet] [Masters thesis]. Louisiana State University; 2013. [cited 2019 Aug 23]. Available from: etd-03182013-190045 ; https://digitalcommons.lsu.edu/gradschool_theses/1540.

Council of Science Editors:

Maier CA. Palate shape and depth : a shape matching and machine learning method for assessment of ancestry from skeletal remains. [Masters Thesis]. Louisiana State University; 2013. Available from: etd-03182013-190045 ; https://digitalcommons.lsu.edu/gradschool_theses/1540

University of California – Merced

24. Hu, Zhe. Camera Shake Removal From One Single Image.

Degree: Electrical Engineering and Computer Science, 2015, University of California – Merced

URL: http://www.escholarship.org/uc/item/9p46c1k2

► Image blur is one of the most fundamental and challenging problems in photography. It causes significant image degradation, especially in the low light conditions where… (more)

Subjects/Keywords: Computer science; Camera shake removal; depth estimation; good region; Light streaks; Non-uniform model; Prior

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Hu, Z. (2015). Camera Shake Removal From One Single Image. (Thesis). University of California – Merced. Retrieved from http://www.escholarship.org/uc/item/9p46c1k2

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Hu, Zhe. “Camera Shake Removal From One Single Image.” 2015. Thesis, University of California – Merced. Accessed August 23, 2019. http://www.escholarship.org/uc/item/9p46c1k2.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Hu, Zhe. “Camera Shake Removal From One Single Image.” 2015. Web. 23 Aug 2019.

Vancouver:

Hu Z. Camera Shake Removal From One Single Image. [Internet] [Thesis]. University of California – Merced; 2015. [cited 2019 Aug 23]. Available from: http://www.escholarship.org/uc/item/9p46c1k2.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Hu Z. Camera Shake Removal From One Single Image. [Thesis]. University of California – Merced; 2015. Available from: http://www.escholarship.org/uc/item/9p46c1k2

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

IUPUI

25. Chowdhury, Prodipto. Estimation of Defocus Blur in Virtual Environments Comparing Graph Cuts and Convolutional Neural Network.

Degree: 2018, IUPUI

URL: http://hdl.handle.net/1805/17925

►

Indiana University-Purdue University Indianapolis (IUPUI)

Depth estimation is one of the most important problems in computer vision. It has attracted a lot of attention because… (more)

Subjects/Keywords: 3D; Graph cuts; Depth estimation; Deep learning; Virtual environments; Convolutional neural network; Defocus blur

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APA (6^th Edition):

Chowdhury, P. (2018). Estimation of Defocus Blur in Virtual Environments Comparing Graph Cuts and Convolutional Neural Network. (Thesis). IUPUI. Retrieved from http://hdl.handle.net/1805/17925

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Chowdhury, Prodipto. “Estimation of Defocus Blur in Virtual Environments Comparing Graph Cuts and Convolutional Neural Network.” 2018. Thesis, IUPUI. Accessed August 23, 2019. http://hdl.handle.net/1805/17925.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Chowdhury, Prodipto. “Estimation of Defocus Blur in Virtual Environments Comparing Graph Cuts and Convolutional Neural Network.” 2018. Web. 23 Aug 2019.

Vancouver:

Chowdhury P. Estimation of Defocus Blur in Virtual Environments Comparing Graph Cuts and Convolutional Neural Network. [Internet] [Thesis]. IUPUI; 2018. [cited 2019 Aug 23]. Available from: http://hdl.handle.net/1805/17925.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Chowdhury P. Estimation of Defocus Blur in Virtual Environments Comparing Graph Cuts and Convolutional Neural Network. [Thesis]. IUPUI; 2018. Available from: http://hdl.handle.net/1805/17925

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Edinburgh

26. Horna Carranza, Luis Alberto. Specialised global methods for binocular and trinocular stereo matching.

Degree: PhD, 2017, University of Edinburgh

URL: http://hdl.handle.net/1842/29017

► The problem of estimating depth from two or more images is a fundamental problem in computer vision, which is commonly referred as to stereo matching.… (more)

Subjects/Keywords: depth estimation; stereo matching; binocular stereo matching algorithm; 3D; trinocular; trinocular algorithms; binocular algorithms

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APA (6^th Edition):

Horna Carranza, L. A. (2017). Specialised global methods for binocular and trinocular stereo matching. (Doctoral Dissertation). University of Edinburgh. Retrieved from http://hdl.handle.net/1842/29017

Chicago Manual of Style (16^th Edition):

Horna Carranza, Luis Alberto. “Specialised global methods for binocular and trinocular stereo matching.” 2017. Doctoral Dissertation, University of Edinburgh. Accessed August 23, 2019. http://hdl.handle.net/1842/29017.

MLA Handbook (7^th Edition):

Horna Carranza, Luis Alberto. “Specialised global methods for binocular and trinocular stereo matching.” 2017. Web. 23 Aug 2019.

Vancouver:

Horna Carranza LA. Specialised global methods for binocular and trinocular stereo matching. [Internet] [Doctoral dissertation]. University of Edinburgh; 2017. [cited 2019 Aug 23]. Available from: http://hdl.handle.net/1842/29017.

Council of Science Editors:

Horna Carranza LA. Specialised global methods for binocular and trinocular stereo matching. [Doctoral Dissertation]. University of Edinburgh; 2017. Available from: http://hdl.handle.net/1842/29017

27. Javidnia, Hossein. Contributions to the measurement of depth in consumer imaging.

Degree: 2018, NUI Galway

URL: http://hdl.handle.net/10379/7398

► This thesis aims to examine and investigate methods that could potentially utilize images captured by consumer cameras such as smartphones to estimate depth and generate… (more)

Subjects/Keywords: Depth estimation; Consumer imaging; 3D reconstruction; Electrical and Electronic Engineering; Engineering and Informatics

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Javidnia, H. (2018). Contributions to the measurement of depth in consumer imaging. (Thesis). NUI Galway. Retrieved from http://hdl.handle.net/10379/7398

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Javidnia, Hossein. “Contributions to the measurement of depth in consumer imaging.” 2018. Thesis, NUI Galway. Accessed August 23, 2019. http://hdl.handle.net/10379/7398.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Javidnia, Hossein. “Contributions to the measurement of depth in consumer imaging.” 2018. Web. 23 Aug 2019.

Vancouver:

Javidnia H. Contributions to the measurement of depth in consumer imaging. [Internet] [Thesis]. NUI Galway; 2018. [cited 2019 Aug 23]. Available from: http://hdl.handle.net/10379/7398.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Javidnia H. Contributions to the measurement of depth in consumer imaging. [Thesis]. NUI Galway; 2018. Available from: http://hdl.handle.net/10379/7398

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Mid Sweden University

28. Bartosch, Nadine. Correspondence-based pairwise depth estimation with parallel acceleration.

Degree: Information Systems and Technology, 2018, Mid Sweden University

URL: http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-34372

► This report covers the implementation and evaluation of a stereo vision corre- spondence-based depth estimation algorithm on a GPU. The results and feed- back… (more)

▼ This report covers the implementation and evaluation of a stereo vision corre- spondence-based depth estimation algorithm on a GPU. The results and feed- back are used for a Multi-view camera system in combination with Jetson TK1 devices for parallelized image processing and the aim of this system is to esti- mate the depth of the scenery in front of it. The performance of the algorithm plays the key role. Alongside the implementation, the objective of this study is to investigate the advantages of parallel acceleration inter alia the differences to the execution on a CPU which are significant for all the function, the imposed overheads particular for a GPU application like memory transfer from the CPU to the GPU and vice versa as well as the challenges for real-time and concurrent execution. The study has been conducted with the aid of CUDA on three NVIDIA GPUs with different characteristics and with the aid of knowledge gained through extensive literature study about different depth estimation algo- rithms but also stereo vision and correspondence as well as CUDA in general. Using the full set of components of the algorithm and expecting (near) real-time execution is utopic in this setup and implementation, the slowing factors are in- ter alia the semi-global matching. Investigating alternatives shows that results for disparity maps of a certain accuracy are also achieved by local methods like the Hamming Distance alone and by a filter that refines the results. Further- more, it is demonstrated that the kernel launch configuration and the usage of GPU memory types like shared memory is crucial for GPU implementations and has an impact on the performance of the algorithm. Just concurrency proves to be a more complicated task, especially in the desired way of realization. For the future work and refinement of the algorithm it is therefore recommended to invest more time into further optimization possibilities in regards of shared memory and into integrating the algorithm into the actual pipeline.

Subjects/Keywords: Depth estimation; disparity; stereo vision; stereo correspondence; NVIDIA; GPU; CUDA; parallelization; Computer Systems; Datorsystem

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Bartosch, N. (2018). Correspondence-based pairwise depth estimation with parallel acceleration. (Thesis). Mid Sweden University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-34372

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Bartosch, Nadine. “Correspondence-based pairwise depth estimation with parallel acceleration.” 2018. Thesis, Mid Sweden University. Accessed August 23, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-34372.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Bartosch, Nadine. “Correspondence-based pairwise depth estimation with parallel acceleration.” 2018. Web. 23 Aug 2019.

Vancouver:

Bartosch N. Correspondence-based pairwise depth estimation with parallel acceleration. [Internet] [Thesis]. Mid Sweden University; 2018. [cited 2019 Aug 23]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-34372.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Bartosch N. Correspondence-based pairwise depth estimation with parallel acceleration. [Thesis]. Mid Sweden University; 2018. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-34372

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Arizona

29. Salahieh, Basel. Computational Imaging For Miniature Cameras .

Degree: 2015, University of Arizona

URL: http://hdl.handle.net/10150/581305

► Miniature cameras play a key role in numerous imaging applications ranging from endoscopy and metrology inspection devices to smartphones and head-mount acquisition systems. However, due… (more)

▼ Miniature cameras play a key role in numerous imaging applications ranging from endoscopy and metrology inspection devices to smartphones and head-mount acquisition systems. However, due to the physical constraints, the imaging conditions, and the low quality of small optics, their imaging capabilities are limited in terms of the delivered resolution, the acquired depth of field, and the captured dynamic range. Computational imaging jointly addresses the imaging system and the reconstructing algorithms to bypass the traditional limits of optical systems and deliver better restorations for various applications. The scene is encoded into a set of efficient measurements which could then be computationally decoded to output a richer estimate of the scene as compared with the raw images captured by conventional imagers. In this dissertation, three task-based computational imaging techniques are developed to make low-quality miniature cameras capable of delivering realistic high-resolution reconstructions, providing full-focus imaging, and acquiring depth information for high dynamic range objects. For the superresolution task, a non-regularized direct superresolution algorithm is developed to achieve realistic restorations without being penalized by improper assumptions (e.g., optimizers, priors, and regularizers) made in the inverse problem. An adaptive frequency-based filtering scheme is introduced to upper bound the reconstruction errors while still producing more fine details as compared with previous methods under realistic imaging conditions. For the full-focus imaging task, a computational depth-based deconvolution technique is proposed to bring a scene captured by an ordinary fixed-focus camera to a full-focus based on a depth-variant point spread function prior. The ringing artifacts are suppressed on three levels: block tiling to eliminate boundary artifacts, adaptive reference maps to reduce ringing initiated by sharp edges, and block-wise deconvolution or depth-based masking to suppress artifacts initiated by neighboring depth-transition surfaces. Finally for the depth acquisition task, a multi-polarization fringe projection imaging technique is introduced to eliminate saturated points and enhance the fringe contrast by selecting the proper polarized channel measurements. The developed technique can be easily extended to include measurements captured under different exposure times to obtain more accurate shape rendering for very high dynamic range objects. Advisors/Committee Members: Liang, Rongguang (advisor), Rodriguez, Jeffrey J (advisor), Liang, Rongguang (committeemember), Rodriguez, Jeffrey J. (committeemember), Bilgin, Ali (committeemember), Milster, Thomas D. (committeemember).

Subjects/Keywords: Computational Imaging; Deconvolution; Depth Estimation; Image Reconstruction; Superresolution; Electrical & Computer Engineering; Cameras

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Salahieh, B. (2015). Computational Imaging For Miniature Cameras . (Doctoral Dissertation). University of Arizona. Retrieved from http://hdl.handle.net/10150/581305

Chicago Manual of Style (16^th Edition):

Salahieh, Basel. “Computational Imaging For Miniature Cameras .” 2015. Doctoral Dissertation, University of Arizona. Accessed August 23, 2019. http://hdl.handle.net/10150/581305.

MLA Handbook (7^th Edition):

Salahieh, Basel. “Computational Imaging For Miniature Cameras .” 2015. Web. 23 Aug 2019.

Vancouver:

Salahieh B. Computational Imaging For Miniature Cameras . [Internet] [Doctoral dissertation]. University of Arizona; 2015. [cited 2019 Aug 23]. Available from: http://hdl.handle.net/10150/581305.

Council of Science Editors:

Salahieh B. Computational Imaging For Miniature Cameras . [Doctoral Dissertation]. University of Arizona; 2015. Available from: http://hdl.handle.net/10150/581305

UCLA

30. Yang, Yanchao. Unsupervised Learning for Object Representations by Watching and Moving.

Degree: Computer Science, 2019, UCLA

URL: http://www.escholarship.org/uc/item/9sb7z9g4

► The power of deep neural networks comes mainly from huge labeled datasets. Even though it shines on many computer vision tasks, supervised learning bears little… (more)

Subjects/Keywords: Computer science; Adversarial Contextual Model; Conditional Prior; Depth Estimation; Object Detection; Optical Flow; Unsupervised Learning

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Yang, Y. (2019). Unsupervised Learning for Object Representations by Watching and Moving. (Thesis). UCLA. Retrieved from http://www.escholarship.org/uc/item/9sb7z9g4

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Yang, Yanchao. “Unsupervised Learning for Object Representations by Watching and Moving.” 2019. Thesis, UCLA. Accessed August 23, 2019. http://www.escholarship.org/uc/item/9sb7z9g4.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Yang, Yanchao. “Unsupervised Learning for Object Representations by Watching and Moving.” 2019. Web. 23 Aug 2019.

Vancouver:

Yang Y. Unsupervised Learning for Object Representations by Watching and Moving. [Internet] [Thesis]. UCLA; 2019. [cited 2019 Aug 23]. Available from: http://www.escholarship.org/uc/item/9sb7z9g4.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Yang Y. Unsupervised Learning for Object Representations by Watching and Moving. [Thesis]. UCLA; 2019. Available from: http://www.escholarship.org/uc/item/9sb7z9g4

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Open Access Theses and Dissertations