Fast GPU Accelerated Stereo Correspondence for Embedded Surveillance Camera Systems
(2015) In LU-CS-EX 2015-33 EDA920 20151Department of Computer Science
- Abstract (Swedish)
- Many surveillance applications could benefit from the use of stereo cam-
eras for depth perception. While state-of-the-art methods provide high quality scene depth information, many of the methods are very time consuming and not suitable for real-time usage in limited embedded systems. This study was conducted to examine stereo correlation methods to find a suitable algorithm for real-time or near real-time depth perception through disparity maps in a stereo video surveillance camera with an embedded GPU. Moreover, novel refinements and alternations was investigated to further improve performance and quality. Quality tests were conducted in Octave while GPU suitability and performance tests were done in C++ with the OpenGL ES 2.0 library.... (More) - Many surveillance applications could benefit from the use of stereo cam-
eras for depth perception. While state-of-the-art methods provide high quality scene depth information, many of the methods are very time consuming and not suitable for real-time usage in limited embedded systems. This study was conducted to examine stereo correlation methods to find a suitable algorithm for real-time or near real-time depth perception through disparity maps in a stereo video surveillance camera with an embedded GPU. Moreover, novel refinements and alternations was investigated to further improve performance and quality. Quality tests were conducted in Octave while GPU suitability and performance tests were done in C++ with the OpenGL ES 2.0 library. The result is a local stereo correlation method using Normalized Cross Correlation together with sparse support windows and a suggested improvement for pixel-wise matching confidence. Applying sparse support windows increased frame rate by 35% with minimal quality penalty as compared to using full support windows. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/7761572
- author
- Andersson Sturén, Vilhelm LU and Hindefelt, Sebastian
- supervisor
- organization
- course
- EDA920 20151
- year
- 2015
- type
- H3 - Professional qualifications (4 Years - )
- subject
- keywords
- disparity map, 3D vision, camera surveillance, images and graphics, surveillance, Stereo correspondence, GPU accelerated, fast
- publication/series
- LU-CS-EX 2015-33
- report number
- LU-CS-EX 2015-33
- ISSN
- 1650-2884
- language
- English
- id
- 7761572
- date added to LUP
- 2015-08-14 10:29:18
- date last changed
- 2015-08-14 10:29:18
@misc{7761572,
abstract = {{Many surveillance applications could benefit from the use of stereo cam-
eras for depth perception. While state-of-the-art methods provide high quality scene depth information, many of the methods are very time consuming and not suitable for real-time usage in limited embedded systems. This study was conducted to examine stereo correlation methods to find a suitable algorithm for real-time or near real-time depth perception through disparity maps in a stereo video surveillance camera with an embedded GPU. Moreover, novel refinements and alternations was investigated to further improve performance and quality. Quality tests were conducted in Octave while GPU suitability and performance tests were done in C++ with the OpenGL ES 2.0 library. The result is a local stereo correlation method using Normalized Cross Correlation together with sparse support windows and a suggested improvement for pixel-wise matching confidence. Applying sparse support windows increased frame rate by 35% with minimal quality penalty as compared to using full support windows.}},
author = {{Andersson Sturén, Vilhelm and Hindefelt, Sebastian}},
issn = {{1650-2884}},
language = {{eng}},
note = {{Student Paper}},
series = {{LU-CS-EX 2015-33}},
title = {{Fast GPU Accelerated Stereo Correspondence for Embedded Surveillance Camera Systems}},
year = {{2015}},
}