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http://dx.doi.org/10.6109/JKIICE.2009.13.6.1194

Weighted cost aggregation approach for depth extraction of stereo images  

Yoon, Hee-Joo (부산대학교 컴퓨터공학과)
Cha, Eui-Young (부산대학교 컴퓨터공학과)
Abstract
Stereo vision system is useful method for inferring 3D depth information from two or more images. So it has been the focus of attention in this field for a long time. Stereo matching is the process of finding correspondence points in two or more images. A central problem in a stereo matching is that it is difficult to satisfy both the computation time problem and accuracy at the same time. To resolve this problem, we proposed a new stereo matching technique using weighted cost aggregation. To begin with, we extract the weight in given stereo images based on features. We compute the costs of the pixels in a given window using correlation of weighted color and brightness information. Then, we match pixels in a given window between the reference and target images of a stereo pair. To demonstrate the effectiveness of the algorithm, we provide experimental data from several synthetic and real scenes. The experimental results show the improved accuracy of the proposed method.
Keywords
Disparity map; depth extraction; stereo matching; weighted matching; cost aggregation;
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1 YongSheng Chen, YiPing Hung, 'Fast Block Matching Algorithm Based on the Winner- Update Strategy,' IEEE Transactions on Image Processing, Vol. 10, Issue 8, Page(s) : 1212-1222, August 2001   DOI   ScienceOn
2 Kuk-Jin Yoon, In So Kweon, 'Adaptive support-weight approach for correspondence search', IEEE Transaction on Pattern Analysis and Machine Intelligence, Vol.28, Issue 4, Page(s):650-656, April 2006   DOI   ScienceOn
3 Yihua Xu, Dongsheung Wang, 'Stereo Computation using Radial Adaptive Windows', IEEE Pattern Recognition Proceedings 16th International Conference, Vol. 3, Page(s) : 595-598, August 2002
4 Yilei Zhang, Minglun Gong, Yee-Hong Yang, 'Local Stereo Matching with 3D Adaptive Cost Aggregation for Slanted Surface Modeling and Sub-Pixel Accuracy,' IEEE, Pattern Recognition 2008 ICPR 19th International Conference, Vol.10, Page(s):1-4, Dec 2008
5 T. Kanade, M. Okutomi, 'A stereo matching algorithm with an adaptive window : theory and experiment', IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.16, Issue 9, Page(s) : 920-932, September 1999   DOI   ScienceOn
6 Clark F. Olson, 'Maximum-Likelihood Image Matching,' IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 24, Issue 6, Page(s) : 853-857, June 2002   DOI   ScienceOn
7 Federico Tomabari, Stefano Mattoccia, Luigi Di Stefano, 'Segmentation-based adaptive support for accurate stereo correspondence,' PSIVT, pp.427-438, 2007