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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.
Runtime Analysis of GPU-Based Stereo Matching
Digital Object Identifier (DOI) : 10.14569/IJACSA.2015.061138
Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 6 Issue 11, 2015.
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}
}
