In this paper a stereo algorithm suitable for implementation on commodity graphics hardware is presented. This is important since it allows to free up the main processor for other tasks including high-level interpretation of the stereo results. Our algorithm relies on the traditional sum-of-square-differences (SSD) dissimilarity measure between correlation windows. To achieve good results close to depth discontinuities as well as on low texture areas a multi-resolution approach is used. The approach efficiently combines SSD measurements for windows of different sizes. Our implementation running on an NVIDIA GeForce4 graphics card achieves 50-70M disparity evaluations per second including all the overhead to download images and read-back the disparity map, which is equivalent to the fastest commercial CPU implementations available. An important advantage of our approach is that rectification is not necessary so that correspondences can just as easily be obtained for images that contain the epipoles. Another advantage is that this approach can easily be extended to multi-baseline stereo.
|Journal||Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition|
|State||Published - 2003|
|Event||2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Madison, WI, United States|
Duration: Jun 18 2003 → Jun 20 2003
ASJC Scopus subject areas
- Computer Vision and Pattern Recognition