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The Science and Information (SAI) Organization publishes open-access peer-reviewed journals in computer science and artificial intelligence.

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Research Article | Open Access |

Runtime Analysis of GPU-Based Stereo Matching

Author 1: Christian Zentner Author 2: Yan Liu
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 6, No. 11 · Published 2015

DOI: https://doi.org/10.14569/IJACSA.2015.061138

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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

How to Cite this Article

Zentner, C., & Liu, Y. (2015). Runtime Analysis of GPU-Based Stereo Matching. International Journal of Advanced Computer Science and Applications, 6(11). https://doi.org/10.14569/IJACSA.2015.061138

Zentner, Christian, and Yan Liu. "Runtime Analysis of GPU-Based Stereo Matching." International Journal of Advanced Computer Science and Applications, vol. 6, no. 11, 2015, https://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},
  volume    = {6},
  number    = {11},
  year      = {2015},
  publisher = {The Science and Information Organization},
  author    = {Christian Zentner and Yan Liu},
  doi       = {10.14569/IJACSA.2015.061138},
  url       = {https://doi.org/10.14569/IJACSA.2015.061138}
}

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