Advanced search options

Advanced Search Options 🞨

Browse by author name (“Author name starts with…”).

Find ETDs with:

in
/  
in
/  
in
/  
in

Written in Published in Earliest date Latest date

Sorted by

Results per page:

Language: English

You searched for subject:(SLIC). One record found.

Search Limiters

Last 2 Years | English Only

No search limiters apply to these results.

▼ Search Limiters

1. Wälivaara, Marcus. General Object Detection Using Superpixel Preprocessing.

Degree: Computer Vision, 2017, Linköping University

The objective of this master’s thesis work is to evaluate the potential benefit of a superpixel preprocessing step for general object detection in a traffic environment. The various effects of different superpixel parameters on object detection performance, as well as the benefit of including depth information when generating the superpixels are investigated. In this work, three superpixel algorithms are implemented and compared, including a proposal for an improved version of the popular Spectral Linear Iterative Clustering superpixel algorithm (SLIC). The proposed improved algorithm utilises a coarse-to-fine approach which outperforms the original SLIC for high-resolution images. An object detection algorithm is also implemented and evaluated. The algorithm makes use of depth information obtained by a stereo camera to extract superpixels corresponding to foreground objects in the image. Hierarchical clustering is then applied, with the segments formed by the clustered superpixels indicating potential objects in the input image. The object detection algorithm managed to detect on average 58% of the objects present in the chosen dataset. It performed especially well for detecting pedestrians or other objects close to the car. Altering the density distribution of the superpixels in the image yielded an increase in detection rate, and could be achieved both with or without utilising depth information. It was also shown that the use of superpixels greatly reduces the amount of computations needed for the algorithm, indicating that a real-time implementation is feasible.

Subjects/Keywords: superpixels; SLIC; coarse-to-fine; segmentation; general object detection; cityscapes; traffic; image processing; clustering; Computer Vision and Robotics (Autonomous Systems); Datorseende och robotik (autonoma system)

…5.1.1 SLIC . . . . . . . . . . . . . . . . . . . . . . 5.1.2 CTF… …5.1.3 CTF-SLIC . . . . . . . . . . . . . . . . . . . 5.2 Results for Object Detection… …Iterative Clustering (SLIC), proposed by Achanta et al. in 2010 [1]. The… …performance have been suggested. Examples include algorithms such as S-SLIC [9] and gSLIC… …x5B;17], which successfully enable the computation of SLIC superpixels in real-time… 

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Wälivaara, M. (2017). General Object Detection Using Superpixel Preprocessing. (Thesis). Linköping University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-140874

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):

Wälivaara, Marcus. “General Object Detection Using Superpixel Preprocessing.” 2017. Thesis, Linköping University. Accessed May 09, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-140874.

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

MLA Handbook (7th Edition):

Wälivaara, Marcus. “General Object Detection Using Superpixel Preprocessing.” 2017. Web. 09 May 2021.

Vancouver:

Wälivaara M. General Object Detection Using Superpixel Preprocessing. [Internet] [Thesis]. Linköping University; 2017. [cited 2021 May 09]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-140874.

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

Council of Science Editors:

Wälivaara M. General Object Detection Using Superpixel Preprocessing. [Thesis]. Linköping University; 2017. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-140874

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

.