A Very Fast Census-Based Stereo Matching Implementation on a Graphics Processing Unit
Abstract
In this paper a very fast graphics processing unit implementation of a local, census-correlation-based stereo matching algorithm is presented. In comparison to absolute or squared difference correlation techniques, the census transform is computational more expensive which led to the motivation of a GPU-based implementation. Due to the parallel architecture of modern graphics cards, complex algorithms can be executed very efficiently. Thus, this work deals with the question how to use a GPU for high speed and high quality stereo matching. The proposed implementation achieves 75.7 fps at an image resolution of 640 × 480 and a disparity search range of 50 on a NVIDIA GeForce GTX 280 graphics card.
Cite
Text
Weber et al. "A Very Fast Census-Based Stereo Matching Implementation on a Graphics Processing Unit." IEEE/CVF International Conference on Computer Vision Workshops, 2009. doi:10.1109/ICCVW.2009.5457622Markdown
[Weber et al. "A Very Fast Census-Based Stereo Matching Implementation on a Graphics Processing Unit." IEEE/CVF International Conference on Computer Vision Workshops, 2009.](https://mlanthology.org/iccvw/2009/weber2009iccvw-very/) doi:10.1109/ICCVW.2009.5457622BibTeX
@inproceedings{weber2009iccvw-very,
title = {{A Very Fast Census-Based Stereo Matching Implementation on a Graphics Processing Unit}},
author = {Weber, Michael and Humenberger, Martin and Kubinger, Wilfried},
booktitle = {IEEE/CVF International Conference on Computer Vision Workshops},
year = {2009},
pages = {786-793},
doi = {10.1109/ICCVW.2009.5457622},
url = {https://mlanthology.org/iccvw/2009/weber2009iccvw-very/}
}