Journal
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
Volume 41, Issue 5, Pages 1203-1212Publisher
IEEE COMPUTER SOC
DOI: 10.1109/TPAMI.2018.2819662
Keywords
Stereoscopic image; disparity map; radiometric change; coherency sensitive hashing; convex plane refinement
Funding
- Institute for Information & communications Technology Promotion(IITP)
- Commercializations Promotion Agency for R&D Outcomes(COMPA)
- National Research Foundation of Korea - Korea government (MSIP) [R0190-16-2034, 2016K000202, NRF-2014R1A2A1A11049986]
- Institute for Information & Communication Technology Planning & Evaluation (IITP), Republic of Korea [R0190-16-2034] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
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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.
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