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Patchmatch-Based Robust Stereo Matching Under Radiometric Changes.
- Source :
-
IEEE Transactions on Pattern Analysis & Machine Intelligence . May2019, Vol. 41 Issue 5, p1203-1212. 10p. - Publication Year :
- 2019
-
Abstract
- In the real world, the two challenges of stereo vision system include a robust system under various radiometric changes and real-time process. To extract depth information from stereoscopic images, this paper proposes Patchmatch-based robust and fast stereo matching under radiometric changes. For this, a cost function was designed and minimized for estimating an accurate disparity map. Specifically, we used a prior probability to minimize the occlusion region and a smoothness term that considers convexity of objects to extract a fine disparity map. For evaluating the performance of the proposed scheme, we used Middlebury stereo data sets with radiometric changes. The experimental result showed that the proposed method outperforms state-of-the-art methods by up to 3.35 percent better and a range of 4.71 - 27.24 times faster result in terms of bad pixel error and processing time, respectively. Therefore, we believe that the proposed scheme can be a useful tool for computer vision-based applications. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 01628828
- Volume :
- 41
- Issue :
- 5
- Database :
- Academic Search Index
- Journal :
- IEEE Transactions on Pattern Analysis & Machine Intelligence
- Publication Type :
- Academic Journal
- Accession number :
- 135773539
- Full Text :
- https://doi.org/10.1109/TPAMI.2018.2819662