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DOI: 10.14569/IJACSA.2015.061138
PDF

Runtime Analysis of GPU-Based Stereo Matching

Author 1: Christian Zentner
Author 2: Yan Liu

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 6 Issue 11, 2015.

  • Abstract and Keywords
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Abstract: This paper elaborates on the possibility to leverage the highly parallel nature of GPUs to implement more efficient stereo matching algorithms. Different algorithms have been implemented and compared on the CPU and the GPU in order to show the speedup gained by moving the computation to the graphics card. The results were evaluated for accuracy using the test available on the Middlebury website for stereo vision. An assessment of the runtime performance was done by a script which examined the runtime behaviour of the individual steps of the stereo matching algorithm.

Keywords: stereo matching; GPU computing; runtime analysis; computer vision; image processing

Christian Zentner and Yan Liu, “Runtime Analysis of GPU-Based Stereo Matching” International Journal of Advanced Computer Science and Applications(IJACSA), 6(11), 2015. http://dx.doi.org/10.14569/IJACSA.2015.061138

@article{Zentner2015,
title = {Runtime Analysis of GPU-Based Stereo Matching},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2015.061138},
url = {http://dx.doi.org/10.14569/IJACSA.2015.061138},
year = {2015},
publisher = {The Science and Information Organization},
volume = {6},
number = {11},
author = {Christian Zentner and Yan Liu}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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