Patchmatch-based Robust Stereo Matching under Radiometric Changes
- Authors
- Lim, J.; Lee, S.
- Issue Date
- May-2019
- Publisher
- IEEE Computer Society
- Keywords
- Stereoscopic image; disparity map; radiometric change; coherency sensitive hashing; convex plane refinement
- Citation
- IEEE Transactions on Pattern Analysis and Machine Intelligence, v.41, no.5, pp 1203 - 1212
- Pages
- 10
- Journal Title
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Volume
- 41
- Number
- 5
- Start Page
- 1203
- End Page
- 1212
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/44819
- DOI
- 10.1109/TPAMI.2018.2819662
- ISSN
- 0162-8828
1939-3539
- 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% 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. IEEE
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Collections - Graduate School of Advanced Imaging Sciences, Multimedia and Film > Department of Imaging Science and Arts > 1. Journal Articles
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