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Depth Estimation from Stereo Images based on Adaptive Weight and Segmentation
Abstract Stereo vision is one of the most researched areas to develop human like vision capability into machines for the purpose of automatic navigation and reconstruction of the real world from images. Point correspondence matching for disparity map calculation is a vital research issue of stereo vision system. Window-based cost aggregation methods used for the correspondence problem have attracted researches as it can be implemented in real time. In this paper, a new hybrid cost aggregation strategy for similarity evaluation based on adaptive weight and color segmentation of stereo image is proposed. In this strategy, pixels which lie on same segment and are spatially closer are given higher weight. Experimental results show that the proposed method is effective in improving overall disparity map and at depth discontinuity.
Depth Estimation from Stereo Images based on Adaptive Weight and Segmentation
Abstract Stereo vision is one of the most researched areas to develop human like vision capability into machines for the purpose of automatic navigation and reconstruction of the real world from images. Point correspondence matching for disparity map calculation is a vital research issue of stereo vision system. Window-based cost aggregation methods used for the correspondence problem have attracted researches as it can be implemented in real time. In this paper, a new hybrid cost aggregation strategy for similarity evaluation based on adaptive weight and color segmentation of stereo image is proposed. In this strategy, pixels which lie on same segment and are spatially closer are given higher weight. Experimental results show that the proposed method is effective in improving overall disparity map and at depth discontinuity.
Depth Estimation from Stereo Images based on Adaptive Weight and Segmentation
Verma, R. (author) / Singh, H. S. (author) / Verma, A. K. (author)
Journal of The Institution of Engineers (India): Series B ; 93 ; 223-229
2012-12-01
7 pages
Article (Journal)
Electronic Resource
English
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