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Delft University of Technology
1.
Arapakis, Takis (author); van Heerden, Natasja (author); Rodriguez-Mon Barrera, Guillermo (author); Wang, Qu (author).
Digitizing Real-World Scenes from Images.
Degree: 2018, Delft University of Technology
URL: http://resolver.tudelft.nl/uuid:103f2d94-cc84-4582-a25f-a0fc11461f18 
► 3D computer models are starting to play a more and more important role in our society. Realworldsituations are often too complex to explain in a…
(more)
▼ 3D computer models are starting to play a more and more important role in our society. Realworldsituations are often too complex to explain in a 2D map and also the interest in virtualreality, serious gaming and other technologies that can be based on 3D computer models, isgrowing.
Synthesis Project 2018
Geomatics
Advisors/Committee Members: Nan, Liangliang (mentor), Peters, Ravi (mentor), Delft University of Technology (degree granting institution).
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APA (6th Edition):
Arapakis, Takis (author); van Heerden, Natasja (author); Rodriguez-Mon Barrera, Guillermo (author); Wang, Q. (. (2018). Digitizing Real-World Scenes from Images. (Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:103f2d94-cc84-4582-a25f-a0fc11461f18
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Arapakis, Takis (author); van Heerden, Natasja (author); Rodriguez-Mon Barrera, Guillermo (author); Wang, Qu (author). “Digitizing Real-World Scenes from Images.” 2018. Thesis, Delft University of Technology. Accessed March 09, 2021.
http://resolver.tudelft.nl/uuid:103f2d94-cc84-4582-a25f-a0fc11461f18.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Arapakis, Takis (author); van Heerden, Natasja (author); Rodriguez-Mon Barrera, Guillermo (author); Wang, Qu (author). “Digitizing Real-World Scenes from Images.” 2018. Web. 09 Mar 2021.
Vancouver:
Arapakis, Takis (author); van Heerden, Natasja (author); Rodriguez-Mon Barrera, Guillermo (author); Wang Q(. Digitizing Real-World Scenes from Images. [Internet] [Thesis]. Delft University of Technology; 2018. [cited 2021 Mar 09].
Available from: http://resolver.tudelft.nl/uuid:103f2d94-cc84-4582-a25f-a0fc11461f18.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Arapakis, Takis (author); van Heerden, Natasja (author); Rodriguez-Mon Barrera, Guillermo (author); Wang Q(. Digitizing Real-World Scenes from Images. [Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:103f2d94-cc84-4582-a25f-a0fc11461f18
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Delft University of Technology
2.
Alexandridis, Vasileios (author).
Automatic detection of waterbeds in shallow muddy water bodies in the Netherlands using green LiDAR.
Degree: 2020, Delft University of Technology
URL: http://resolver.tudelft.nl/uuid:acbd73bf-3547-456b-8f9d-4b72d5b7b54a
► Bathymetric Airborne LiDAR technology is used to map the depth of water bodies. It uses a green light sensor which is able to penetrate the…
(more)
▼ Bathymetric Airborne LiDAR
technology is used to map the depth of water bodies. It uses a green light sensor which is able to penetrate the water surface and reach the bottom part of the interesting water areas. However, water conditions affect the capability of the green laser penetration. Factors such as the water clarity, the water turbidity (waves) and the vegetation are some of the crucial restrictions for green light to penetrate the water; particularly in shallow inland water areas. This research examined the capability of green LiDAR data to improve the bathymetric surveys in case of muddy and shallow inland Dutch water bodies. The potential of green LiDAR increases as the monitoring of water depths is getting easier, faster and more efficiently in terms of cost than manual GPS measurements. The main challenges of this thesis are concentrated both on the existence of various sparse and dense parts in the point-cloud and on the limitations of the data in terms of quality due to the not ideal water conditions. Specifically, this thesis presents a workflow with required procedures that aim to process a raw green LiDAR point clouds of water bodies and then classify them into three classes: water surface, underwater and bottom points. Pulse and Neighbourhood based algorithms were implemented in order to perform a classification process with high level of automation. Point characteristics such as intensity, number of returns, return number were analysed per pulse. Voxelization was used as a spatial method to divide the 3D space into water columns (3D Voxels). The spatial distribution of the water points into the water columns was examined based on different factors such as elevation, density, intensity. By comparing and partially combining those methods the detection process was improved to deal with shallow and muddy water bodies. A classification confidence value was calculated and stored for each potential bottom point. The resulting output is a classified green LiDAR point cloud based on the confidence values. Using elevation, density and confidence values, raster DTMs with multiple bands were created for each water body. To sum up, this thesis proposed an efficient workflow to process and automatically classify green LiDAR water-body data using both voxel and pulse based methods.
Advisors/Committee Members: Peters, Ravi (mentor), Stoter, Jantien (graduation committee), Delft University of Technology (degree granting institution).
Subjects/Keywords: Green Bathymetric LiDAR; Pulse-based method; Voxelization; Waterbody; Point cloud data; Classification
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APA (6th Edition):
Alexandridis, V. (. (2020). Automatic detection of waterbeds in shallow muddy water bodies in the Netherlands using green LiDAR. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:acbd73bf-3547-456b-8f9d-4b72d5b7b54a
Chicago Manual of Style (16th Edition):
Alexandridis, Vasileios (author). “Automatic detection of waterbeds in shallow muddy water bodies in the Netherlands using green LiDAR.” 2020. Masters Thesis, Delft University of Technology. Accessed March 09, 2021.
http://resolver.tudelft.nl/uuid:acbd73bf-3547-456b-8f9d-4b72d5b7b54a.
MLA Handbook (7th Edition):
Alexandridis, Vasileios (author). “Automatic detection of waterbeds in shallow muddy water bodies in the Netherlands using green LiDAR.” 2020. Web. 09 Mar 2021.
Vancouver:
Alexandridis V(. Automatic detection of waterbeds in shallow muddy water bodies in the Netherlands using green LiDAR. [Internet] [Masters thesis]. Delft University of Technology; 2020. [cited 2021 Mar 09].
Available from: http://resolver.tudelft.nl/uuid:acbd73bf-3547-456b-8f9d-4b72d5b7b54a.
Council of Science Editors:
Alexandridis V(. Automatic detection of waterbeds in shallow muddy water bodies in the Netherlands using green LiDAR. [Masters Thesis]. Delft University of Technology; 2020. Available from: http://resolver.tudelft.nl/uuid:acbd73bf-3547-456b-8f9d-4b72d5b7b54a
Delft University of Technology
3.
Wang, Qu (author).
3D breakline extraction from point clouds with the Medial Axis Transform.
Degree: 2019, Delft University of Technology
URL: http://resolver.tudelft.nl/uuid:ba8e4bf4-e473-410b-a1f0-ef48e9c2fbf3
► This project develop a new method to generate breakline from the point cloud directly with the MAT. The breakline is a structured line of the…
(more)
▼ This project develop a new method to generate breakline from the point cloud directly with the MAT. The breakline is a structured line of the object surface which has high curvature. Meanwhile, the reciprocal of the medial edge ball's radius can represent the point with high curvature, which is the fundamental idea of this project. The key parts of the method are: (a) with the help of MAT detecting candidate points having high curvature; (b) connect the candidate points to get breaklines with graph theory or polynomial fitting. The topology of the breakline is considered. In addition, this project also provides the polyline simplification and smoothing. In the resulting breakline, 27/32 are true positive. In general, the average correctness is 97% and 96%, the average quality is 90.67% and 91.19%, and the average completeness is 93.84% and 93.92% for valley and ridge. Most of accuracy parameters are above 80%. The accuracy is high. As to the precision, the average polyline precision is 0.3 and 0.23, and the average vertex precision is 1.14 meter and 1.12 meter. Comparing with the point density 2 pts/m2. 25 of 27 breaklines' polyline precision is better than 0.5. 16 of 27 breakline's vertex precision is better than 1.0; and 23 of 26 is better than 1.5. The precision is also good. The source code is on Github: https://github.com/qq2012/geoflow-nodes.
Architecture, Urbanism and Building Sciences | Management in the Built Environment
Advisors/Committee Members: Peters, Ravi (mentor), Ledoux, Hugo (graduation committee), Delft University of Technology (degree granting institution).
Subjects/Keywords: breakline; mountain; Medial Axis Transform; point cloud
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APA (6th Edition):
Wang, Q. (. (2019). 3D breakline extraction from point clouds with the Medial Axis Transform. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:ba8e4bf4-e473-410b-a1f0-ef48e9c2fbf3
Chicago Manual of Style (16th Edition):
Wang, Qu (author). “3D breakline extraction from point clouds with the Medial Axis Transform.” 2019. Masters Thesis, Delft University of Technology. Accessed March 09, 2021.
http://resolver.tudelft.nl/uuid:ba8e4bf4-e473-410b-a1f0-ef48e9c2fbf3.
MLA Handbook (7th Edition):
Wang, Qu (author). “3D breakline extraction from point clouds with the Medial Axis Transform.” 2019. Web. 09 Mar 2021.
Vancouver:
Wang Q(. 3D breakline extraction from point clouds with the Medial Axis Transform. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2021 Mar 09].
Available from: http://resolver.tudelft.nl/uuid:ba8e4bf4-e473-410b-a1f0-ef48e9c2fbf3.
Council of Science Editors:
Wang Q(. 3D breakline extraction from point clouds with the Medial Axis Transform. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:ba8e4bf4-e473-410b-a1f0-ef48e9c2fbf3
Delft University of Technology
4.
Wu, Teng (author).
Visibility Analysis in a Point Cloud based on the Medial Axis Transform.
Degree: 2019, Delft University of Technology
URL: http://resolver.tudelft.nl/uuid:1b2da021-816b-4516-9e4d-e8315707b6fc
► This thesis proposes a novel medial axis transform (MAT) based method to achieve visibility analysis in a point cloud. There are several advantages of this…
(more)
▼ This thesis proposes a novel medial axis transform (MAT) based method to achieve visibility analysis in a point cloud. There are several advantages of this MAT based method. This method avoids surface reconstruction from a point cloud. It also works for the situation when there is surface missing in the input point cloud. For different point cloud datasets such as point cloud generated from meshes, AHN3 point cloud and point cloud generated from dense image matching, this method successfully deliver decent visibility result for all of them. The main challenge overcome in this thesis is the interior and exterior MAT separation. Two approaches, normal reorientation approach and bisector based approach are experimented in the thesis to separate MAT. The normal reorientation approach only works for point cloud generated from meshes. The bisector based approaches works for all the datasets testes. It successfully separates the interior and exterior MAT when there is surfacing missing. To speed up of the query process, spatial index is generated for interior MAT. In this thesis, two spatial indices are implemented, KD-Tree and R-Tree. Due to the limitation of my KD-Tree implementation, the KD-Tree does not improve the running speed obvious. There is a room to improve the KD-Tree implementation. The R-Tree achieves sharply improvement on running time of the queries. For 51567 points, the query based on R-Tree finished in 1880 ms. In a word, this thesis proposed an efficient MAT based method of visibility analysis in a point cloud.
Geomatics
Advisors/Committee Members: Peters, Ravi (mentor), Ledoux, Hugo (graduation committee), Delft University of Technology (degree granting institution).
Subjects/Keywords: point cloud; Visibility analysis; Medial Axis Transform
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APA (6th Edition):
Wu, T. (. (2019). Visibility Analysis in a Point Cloud based on the Medial Axis Transform. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:1b2da021-816b-4516-9e4d-e8315707b6fc
Chicago Manual of Style (16th Edition):
Wu, Teng (author). “Visibility Analysis in a Point Cloud based on the Medial Axis Transform.” 2019. Masters Thesis, Delft University of Technology. Accessed March 09, 2021.
http://resolver.tudelft.nl/uuid:1b2da021-816b-4516-9e4d-e8315707b6fc.
MLA Handbook (7th Edition):
Wu, Teng (author). “Visibility Analysis in a Point Cloud based on the Medial Axis Transform.” 2019. Web. 09 Mar 2021.
Vancouver:
Wu T(. Visibility Analysis in a Point Cloud based on the Medial Axis Transform. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2021 Mar 09].
Available from: http://resolver.tudelft.nl/uuid:1b2da021-816b-4516-9e4d-e8315707b6fc.
Council of Science Editors:
Wu T(. Visibility Analysis in a Point Cloud based on the Medial Axis Transform. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:1b2da021-816b-4516-9e4d-e8315707b6fc
Delft University of Technology
5.
Tryfona, Maya (author).
Bidirectional enrichment of CityGML and Multi-View Stereo Mesh models.
Degree: 2017, Delft University of Technology
URL: http://resolver.tudelft.nl/uuid:560bd9fb-7688-492f-b1c0-799644707be9
► The use of 3D city models has increased the last decades due to the evolution of technology. Their use is related to the need for…
(more)
▼ The use of 3D city models has increased the last decades due to the evolution of
technology. Their use is related to the need for solutions on issues that correspond to the building environment. Modelling aspects, like geometric, semantic information and topology are necessary, in order to provide an integrated result of spatial analysis. The creation of a complete 3D city model that contains all the needed information for an application, is a time consuming and complex process. Furthermore, different 3D city model formats can contain different aspects of the same features. For example, a CityGML model can have the semantic information of a 3D object, while a Multi-View Stereo Mesh model can contain all the geometric and appearance information of the same 3D object. This thesis is documenting the possible enrichments that can be done bidirectionally between these two different 3D city model formats, when both exist for the same entities. Moreover, it presents the exploration of possible automated enrichment methodologies that can enrich each 3D city model automatically with information from the other one. Finally, an automatic bidirectional enrichment methodology is proposed and is implemented on a testing area, provided in the two different 3D city model formats. This method is based on distance computations between the meshes of the two 3D city models, used to match corresponding features, or part of features, in order to segment semantically the Multi-View Stereo Mesh model (roof, wall, road, terrain, uncertain) and transfer texture to the surfaces of the CityGML model that correspond with the surfaces of the Multi-View Stereo Mesh model. In addition, distance computations are performed for the validation of the absence of buildings and the shapes of the roofs in the CityGML model, with respect to the information given from the Multi-View Stereo Mesh model. After the implementation of the proposed methodology, it is found that both 3D city model formats can be used for the proposed enrichments of either 3D city model format. Future improvements are presented for the achievement of using existing information of different formats of 3D city models of the same entities, in order to supplement each 3D city model format with useful information, enhance the performance of spatial analysis and boost the evolution on the use of such models on real life applications.
Advisors/Committee Members: Ledoux, Hugo (mentor), Peters, Ravi (graduation committee), Delft University of Technology (degree granting institution).
Subjects/Keywords: CityGML; MVSM; bidirectional enrichment; 3D city model
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APA ·
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APA (6th Edition):
Tryfona, M. (. (2017). Bidirectional enrichment of CityGML and Multi-View Stereo Mesh models. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:560bd9fb-7688-492f-b1c0-799644707be9
Chicago Manual of Style (16th Edition):
Tryfona, Maya (author). “Bidirectional enrichment of CityGML and Multi-View Stereo Mesh models.” 2017. Masters Thesis, Delft University of Technology. Accessed March 09, 2021.
http://resolver.tudelft.nl/uuid:560bd9fb-7688-492f-b1c0-799644707be9.
MLA Handbook (7th Edition):
Tryfona, Maya (author). “Bidirectional enrichment of CityGML and Multi-View Stereo Mesh models.” 2017. Web. 09 Mar 2021.
Vancouver:
Tryfona M(. Bidirectional enrichment of CityGML and Multi-View Stereo Mesh models. [Internet] [Masters thesis]. Delft University of Technology; 2017. [cited 2021 Mar 09].
Available from: http://resolver.tudelft.nl/uuid:560bd9fb-7688-492f-b1c0-799644707be9.
Council of Science Editors:
Tryfona M(. Bidirectional enrichment of CityGML and Multi-View Stereo Mesh models. [Masters Thesis]. Delft University of Technology; 2017. Available from: http://resolver.tudelft.nl/uuid:560bd9fb-7688-492f-b1c0-799644707be9
Delft University of Technology
6.
Flikweert, Puck (author).
Automatic Extraction of an IndoorGML Navigation Graph from an Indoor Point Cloud.
Degree: 2019, Delft University of Technology
URL: http://resolver.tudelft.nl/uuid:b11f5b57-5362-4b45-bed6-d5bc154d86aa
► Because of urbanisation, more than 50% of the global population now lives in cities, a number that is ever-increasing. This leads to a need for…
(more)
▼ Because of urbanisation, more than 50% of the global population now lives in cities, a number that is ever-increasing. This leads to a need for more dense and complex building constructions, driven by the fact that people are living increasingly close to one another. These structures are often so large that it becomes difficult to navigate in the environment without any assistance. Especially for people with restricted mobility, such as wheelchair users, or the blind or partially sighted, it can pose a challenge to find the best path in a building. Consequently there is a need for navigation graphs that provide a way to structure connectivity information and routes in an indoor environment. Existing methods generally obtain information on the location of various rooms, corridors and their interconnectivity from 2D floor plans or 3D building models. However, these plans and models often were created by the architect when the building was planned, but never updated with new information after the building was built and came into use. Manually updating them is very labour-intensive. Therefore, in this research a method is developed for obtaining a navigation graph from an indoor environment by automatically extracting the information needed from a point cloud. The navigation graph is modelled according to the Open Geospatial Consortium (OGC) standard IndoorGML, which provides a basic structure for indoor navigation. The point clouds used in this research are gathered with a hand-held Mobile Laser Scanner (MLS), which also saves the path (trajectory) taken in the building. This all leads to the main research question: How can a navigation network in IndoorGML format automatically be extracted from a cluttered indoor point cloud and its trajectory? In order to answer this question this research focuses on the detection of doorways, and how they connect indoor spaces, such as rooms and corridors. A new way of door detection is proposed, which is based on the identification of walls using the 3D Medial Axis Transform (MAT) of the point cloud. After this it is explored how the established connectivity relationships can be extended with accessibility information, such as the location of stairs, and the dimensions of doors. Additionally it is researched how a more detailed navigation graph can be created by subdividing large spaces that have multiple connections. In this thesis it is proven that geometric input for a navigation graph can automatically be obtained from a point cloud. 100% of doors could be detected in the dataset that the methods were developed on, and when testing the methods on another point cloud, this number decreased to 70% , due to unforeseen situations. All spaces connected by detected doors, stairways and sloped surfaces were included in the graph, from which a more extensive navigation graph could be produced by subdividing corridors. This final product was compared to networks drawn by humans on a corresponding floor plan, from which it can be concluded that the graph produced by the methodology of…
Advisors/Committee Members: Peters, Ravi (mentor), Díaz-Vilariño, Lucía (graduation committee), Voûte, Robert (graduation committee), Delft University of Technology (degree granting institution).
Subjects/Keywords: indoor navigation; point cloud; IndoorGML; door detection; voxels; laser scanning; 3D Medial Axis Transform; navigation graph
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APA (6th Edition):
Flikweert, P. (. (2019). Automatic Extraction of an IndoorGML Navigation Graph from an Indoor Point Cloud. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:b11f5b57-5362-4b45-bed6-d5bc154d86aa
Chicago Manual of Style (16th Edition):
Flikweert, Puck (author). “Automatic Extraction of an IndoorGML Navigation Graph from an Indoor Point Cloud.” 2019. Masters Thesis, Delft University of Technology. Accessed March 09, 2021.
http://resolver.tudelft.nl/uuid:b11f5b57-5362-4b45-bed6-d5bc154d86aa.
MLA Handbook (7th Edition):
Flikweert, Puck (author). “Automatic Extraction of an IndoorGML Navigation Graph from an Indoor Point Cloud.” 2019. Web. 09 Mar 2021.
Vancouver:
Flikweert P(. Automatic Extraction of an IndoorGML Navigation Graph from an Indoor Point Cloud. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2021 Mar 09].
Available from: http://resolver.tudelft.nl/uuid:b11f5b57-5362-4b45-bed6-d5bc154d86aa.
Council of Science Editors:
Flikweert P(. Automatic Extraction of an IndoorGML Navigation Graph from an Indoor Point Cloud. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:b11f5b57-5362-4b45-bed6-d5bc154d86aa
Delft University of Technology
7.
Griffioen, Simon (author).
A voxel-based methodology to detect (clustered) outliers in aerial lidar point clouds.
Degree: 2018, Delft University of Technology
URL: http://resolver.tudelft.nl/uuid:2ffa73f4-34cc-4ea0-82df-11e61cb47bea
► To obtain 3D information of the Earth’s surface, airborne LiDAR technology is used to quickly capture high-precision measurements of the terrain. Unfortunately, laser scanning techniques…
(more)
▼ To obtain 3D information of the Earth’s surface, airborne LiDAR technology is used to quickly capture high-precision measurements of the terrain. Unfortunately, laser scanning techniques are prone to producing outliers and noise (i.e. wrong measurements). Therefore, a pre-process of the point cloud is required to detect and remove spurious measurements. While outlier detection in datasets has been extensively researched, in 3D point cloud data it is still an ongoing problem. Especially, clustered outliers are hard to detect with previous local-neighborhood based algorithms. This research explores the possibilities of using a voxel-based approach to automatically remove outliers from aerial point clouds. A workflow is designed in which a series of voxel-based operations are integrated, with the aim to detect all types of outliers and minimize false positives. Voxels can be processed more efficiently than 3D points for two reasons: (1) A voxelgrid can be analyzed using efficient image processing techniques; (2) Voxels group inner points before feature extraction using neighborhood operators. Outliers are detected in two steps. First, the source point cloud is voxelized. Secondly, outliers are detected by computing connected components and labeling voxels not connected to the largest region as outliers. Simultaneously, analysis of the point’s local density, shape (planar) and intensity minimize classification of false positives. The presented algorithm generally detects outliers with a higher accuracy than previous local neighborhood-based methods. A comparison with an existing approach shows that more outliers are detected. Above all, clustered outliers are removed. However, some issues can still be improved. First, more research is necessary to classify outliers based on non-arbitrary decisions. This could potentially be improved by introducing supervised learning algorithms. Secondly, more attention is required to process massive point clouds that do not fit in internal memory. This study proposes a possible streaming solution.
Geomatics
Advisors/Committee Members: Peters, Ravi (mentor), Ledoux, Hugo (mentor), Meijers, Martijn (graduation committee), Delft University of Technology (degree granting institution).
Subjects/Keywords: point cloud; aerial lidar; Outlier Detection; voxel; connected components labeling
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APA ·
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APA (6th Edition):
Griffioen, S. (. (2018). A voxel-based methodology to detect (clustered) outliers in aerial lidar point clouds. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:2ffa73f4-34cc-4ea0-82df-11e61cb47bea
Chicago Manual of Style (16th Edition):
Griffioen, Simon (author). “A voxel-based methodology to detect (clustered) outliers in aerial lidar point clouds.” 2018. Masters Thesis, Delft University of Technology. Accessed March 09, 2021.
http://resolver.tudelft.nl/uuid:2ffa73f4-34cc-4ea0-82df-11e61cb47bea.
MLA Handbook (7th Edition):
Griffioen, Simon (author). “A voxel-based methodology to detect (clustered) outliers in aerial lidar point clouds.” 2018. Web. 09 Mar 2021.
Vancouver:
Griffioen S(. A voxel-based methodology to detect (clustered) outliers in aerial lidar point clouds. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2021 Mar 09].
Available from: http://resolver.tudelft.nl/uuid:2ffa73f4-34cc-4ea0-82df-11e61cb47bea.
Council of Science Editors:
Griffioen S(. A voxel-based methodology to detect (clustered) outliers in aerial lidar point clouds. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:2ffa73f4-34cc-4ea0-82df-11e61cb47bea
Delft University of Technology
8.
Christodoulou, Antria (author).
An image-based method for the pairwise registration of mobile laser scanning point clouds.
Degree: 2018, Delft University of Technology
URL: http://resolver.tudelft.nl/uuid:5c1d2d90-8f2f-4dc2-b6c3-d5c635323c35
► In this thesis, an image-based method is proposed for solving the relative translation errors of 3D point clouds collected by Mobile Laser Scanning (MLS) techniques.…
(more)
▼ In this thesis, an image-based method is proposed for solving the relative translation errors of 3D point clouds collected by Mobile Laser Scanning (MLS) techniques. The process of matching 3D point clouds is known as registration. Due to environment-depending limitations of the positioning component of MLS systems, when recording a certain scene more than once, point clouds recorded at different times tend to have mainly positioning distortions. Additionally, due to yaw-angle errors of the recording platform it is possible that the point clouds have small distortions around their Z axis or the point clouds are scanned with fuzziness. This project deals only with the translation errors. Various methods can be found in the literature to perform pair-wise registration of point clouds. Commonly, the challenge of aligning 3D features is tackled in 3D. Only a few techniques for registering point clouds in 2D have being explored. However, the approach presented in this thesis uses the attributes of the 3D points to generate and match 2D-projections, by employing a simple correlation technique instead of matching in 3D. As a result, the developed method depends more on the number of pixels in the 2D-projections and less on the number of points in the point clouds. This leads to a more cost-efficient method in contrast to 3D registration techniques. The method uses this benefit to provide redundant translation parameters for each point cloud pair. Particularly, several images are created from each point cloud tile. The constructed images illustrate the density of the points, the intensity, the gradient of intensity, the depth, the gradient of the depth and the normal vectors of the points. As a result, the translation parameters are retrieved from the matching of various image-techniques and that is how redundant solutions are provided. Next, with the utilization of image-based evaluation criteria the reliable translation parameters are detected and only those are used to compute the final solutions. The reliable estimations are taken into account for the estimation of the final solutions. Since redundant solutions are provided, the confidence levels of each final estimation can be computed. In addition, an indication of robustness showing how many estimations where included for the computation of the final solution is included. As a result, the developed approach is capable of providing information about the precision and reliability of each pairwise registration. In such a way it is known which of the results can be used in a following step, such as a global registration. Furthermore, a 2D Gaussian elliptical fitting is used to obtain sub-pixel accuracy registration results, as the accuracy of the estimations is restricted to the pixel size of the generated images. It is proven that the developed image-based registration method has the capability to produce reliable matches when there is at least some overlap between two overlapping point clouds and corresponding objects between the point clouds are distinct in pairs…
Advisors/Committee Members: van Oosterom, P.J.M. (mentor), Peters, Ravi (mentor), Joosten, Peter (mentor), van Someren, Berry (mentor), Delft University of Technology (degree granting institution).
Subjects/Keywords: point clouds; registration; reliability; Image processing; sub-pixel accuracy
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APA (6th Edition):
Christodoulou, A. (. (2018). An image-based method for the pairwise registration of mobile laser scanning point clouds. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:5c1d2d90-8f2f-4dc2-b6c3-d5c635323c35
Chicago Manual of Style (16th Edition):
Christodoulou, Antria (author). “An image-based method for the pairwise registration of mobile laser scanning point clouds.” 2018. Masters Thesis, Delft University of Technology. Accessed March 09, 2021.
http://resolver.tudelft.nl/uuid:5c1d2d90-8f2f-4dc2-b6c3-d5c635323c35.
MLA Handbook (7th Edition):
Christodoulou, Antria (author). “An image-based method for the pairwise registration of mobile laser scanning point clouds.” 2018. Web. 09 Mar 2021.
Vancouver:
Christodoulou A(. An image-based method for the pairwise registration of mobile laser scanning point clouds. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2021 Mar 09].
Available from: http://resolver.tudelft.nl/uuid:5c1d2d90-8f2f-4dc2-b6c3-d5c635323c35.
Council of Science Editors:
Christodoulou A(. An image-based method for the pairwise registration of mobile laser scanning point clouds. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:5c1d2d90-8f2f-4dc2-b6c3-d5c635323c35
Delft University of Technology
9.
van der Maaden, Jippe (author).
Vario-scale visualization of the AHN2 point cloud.
Degree: 2019, Delft University of Technology
URL: http://resolver.tudelft.nl/uuid:42496941-d12a-48b0-af48-ae4cb12984a6
► LiDAR technologies are used to measure point cloud data of the earth's surface. The usage of LiDAR allows for the fast collections of massive data…
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▼ LiDAR technologies are used to measure point cloud data of the earth's surface. The usage of LiDAR allows for the fast collections of massive data sets. The AHN2 point cloud data set, part of Rijkswaterstaats initiative to map the surface of the Netherlands, contains 639 478 217 460 points. For efficient visualization in web viewers, these massive point clouds are stored in an octree data structure. Visualization through this method has the downside of discretely visualizing the point cloud. These discrete artefacts are referred to as density jumps, and are visible where there is a boundary between blocks retrieved from the octree. These blocks contain different densities because they are retrieved from different levels of the octree. This thesis proposes a continuous visualization method for massive point cloud data sets that aims to eliminate these density jumps. While the continuous visualization of vector data sets has been extensively researched, this is a novel field of research for point cloud data sets. This thesis explores the feasibility of a vario-scale visualization method, and aims to implement it in an existing web viewer architecture. Due to the massive nature of the AHN2 data set, cloud computing and distributed computing techniques are used to imrove the workflow. The presented methodology removes the it{density jumps} by determining an upper density bound for the point cloud density relative to the camera position. Circle packing theory is used to reinforce the upper bound continuously, thus removing artefacts created by discrete density jumps. A proof-of-concept for this theory is implemented in an existing point cloud web viewer architecture.
Advisors/Committee Members: van Oosterom, Peter (mentor), Meijers, Martijn (mentor), van der Heijden, Harry (graduation committee), Peters, Ravi (graduation committee), Delft University of Technology (degree granting institution).
Subjects/Keywords: point cloud; vario-scale; visualization
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APA ·
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APA (6th Edition):
van der Maaden, J. (. (2019). Vario-scale visualization of the AHN2 point cloud. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:42496941-d12a-48b0-af48-ae4cb12984a6
Chicago Manual of Style (16th Edition):
van der Maaden, Jippe (author). “Vario-scale visualization of the AHN2 point cloud.” 2019. Masters Thesis, Delft University of Technology. Accessed March 09, 2021.
http://resolver.tudelft.nl/uuid:42496941-d12a-48b0-af48-ae4cb12984a6.
MLA Handbook (7th Edition):
van der Maaden, Jippe (author). “Vario-scale visualization of the AHN2 point cloud.” 2019. Web. 09 Mar 2021.
Vancouver:
van der Maaden J(. Vario-scale visualization of the AHN2 point cloud. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2021 Mar 09].
Available from: http://resolver.tudelft.nl/uuid:42496941-d12a-48b0-af48-ae4cb12984a6.
Council of Science Editors:
van der Maaden J(. Vario-scale visualization of the AHN2 point cloud. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:42496941-d12a-48b0-af48-ae4cb12984a6
Delft University of Technology
10.
Mulder, Amber (author).
Semantic Segmentation of RGB-Z Aerial Imagery Using Convolutional Neural Networks.
Degree: 2020, Delft University of Technology
URL: http://resolver.tudelft.nl/uuid:b936953b-4c73-4ce1-a897-7da4287ff79a
► Semantic segmentation (or pixel-level classification) of remotely sensed imagery has shown to be useful for applications in fields as mapping of land cover, object detection,…
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▼ Semantic segmentation (or pixel-level classification) of remotely sensed imagery has shown to be useful for applications in fields as mapping of land cover, object detection, change detection and land-use analysis. Deep learning algorithms called convolutional neural networks (CNNs) have shown to outperform traditional computer vision and machine learning approaches in tackling semantic segmentation tasks. Furthermore, addition of height information (Z) to aerial imagery (RGB) is believed to improve segmentation results. However, discussion remains on the following: to what extent height information adds value; the best way to combine RGB information with height information; and what type of height information can best be used. This study aims to answer these questions. In this research work, the CNN architectures FCN-8s, SegNet, U-Net and FuseNet-SF5 are trained to semantically segment 10 cm resolution true ortho imagery of Haarlem, potentially augmented with height information. The outputted topographic maps contain the classes building, road, water and other. Experiments are conducted that allow for the comparison of 1) models trained on RGB and on RGB-Z, 2) models combining RGB and height information through data fusion and through data stacking, and 3) models trained using different types of absolute and relative height approaches. Performances are compared based on scores on the performance measure (mean) intersection over union (IoU) and through visual assessment of outputted prediction maps. The results indicated that on average segmentation performance improves by approximately 1 percent when absolute height information is added. The class building showed to benefit the most from the addition of height information. Furthermore, extracting features from height information in a separate encoder and fusing these into RGB feature maps, led to a higher overall segmentation quality than when height information is provided as a stacked extra band and processed in the same encoder as the RGB information. Finally, models using relative height delivered a higher quality segmentation than when absolute height approaches were used, especially for large objects. The best performing model; FuseNet-SF5 trained on RGB imagery and pixel-level, relative height, retrieved a mean IoU of 0.8427 and IoUs of 0.8744, 0.7865, 0.9131 and 0.7966 for the classes building, road, water and other respectively. This model was able to correctly classify over 90% of the pixels of 67% of all the objects present in the ground truth. Overall, this study showed that, when considering semantic segmentation of aerial RGB imagery, 1) height information can improve segmentation results, 2) adding height information through data fusion can result in a higher segmentation quality than when data stacking is used, and 3) providing relative height to a network, rather than absolute height, can improve semantic segmentation quality.
Geomatics
Advisors/Committee Members: Dukai, Balázs (mentor), Peters, Ravi (graduation committee), Stoter, Jantien (graduation committee), Briels, Sven (graduation committee), Renders, Jean-Michel (graduation committee), Delft University of Technology (degree granting institution).
Subjects/Keywords: Semantic segmentation; Remotely sensed data; Topographic maps; CNN; RGB-Z; Aerial imagery; DSM; Deep learning
Record Details
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Record Details
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APA ·
Chicago ·
MLA ·
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CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Mulder, A. (. (2020). Semantic Segmentation of RGB-Z Aerial Imagery Using Convolutional Neural Networks. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:b936953b-4c73-4ce1-a897-7da4287ff79a
Chicago Manual of Style (16th Edition):
Mulder, Amber (author). “Semantic Segmentation of RGB-Z Aerial Imagery Using Convolutional Neural Networks.” 2020. Masters Thesis, Delft University of Technology. Accessed March 09, 2021.
http://resolver.tudelft.nl/uuid:b936953b-4c73-4ce1-a897-7da4287ff79a.
MLA Handbook (7th Edition):
Mulder, Amber (author). “Semantic Segmentation of RGB-Z Aerial Imagery Using Convolutional Neural Networks.” 2020. Web. 09 Mar 2021.
Vancouver:
Mulder A(. Semantic Segmentation of RGB-Z Aerial Imagery Using Convolutional Neural Networks. [Internet] [Masters thesis]. Delft University of Technology; 2020. [cited 2021 Mar 09].
Available from: http://resolver.tudelft.nl/uuid:b936953b-4c73-4ce1-a897-7da4287ff79a.
Council of Science Editors:
Mulder A(. Semantic Segmentation of RGB-Z Aerial Imagery Using Convolutional Neural Networks. [Masters Thesis]. Delft University of Technology; 2020. Available from: http://resolver.tudelft.nl/uuid:b936953b-4c73-4ce1-a897-7da4287ff79a
. 
Open Access Theses and Dissertations