Stereo matching using gradient similarity and locally adaptive support-weight

被引:89
作者
De-Maeztu, Leonardo [1 ]
Villanueva, Arantxa [1 ]
Cabeza, Rafael [1 ]
机构
[1] Univ Publ Navarra, Dept Elect & Elect Engn, Pamplona 31006, Spain
关键词
Stereo vision; Local correspondence search; Window-based; Adaptive support-weight; Gradient;
D O I
10.1016/j.patrec.2011.06.027
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Due to the similarities between neighbouring pixels as well as the intensity-value differences between corresponding pixels, classical matching measures based on intensity similarity produce slightly imprecise results. In this study, a gradient similarity-matching measure was implemented in a state-of-the-art local stereo-matching method (an adaptive support-weight algorithm). The new matching measure improved the precision of the results over the classical measures. Using the Middlebury stereo benchmark, when high accuracy was required in the disparity results our algorithm consistently outperformed other adaptive support-weight algorithms using different similarity measures, and it was the best local area-based method compared to the permanent Middlebury table entries. (C) 2011 Elsevier B.V. All rights reserved.
引用
收藏
页码:1643 / 1651
页数:9
相关论文
共 19 条
[1]   A pixel dissimilarity measure that is insensitive to image sampling [J].
Birchfield, S ;
Tomasi, C .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1998, 20 (04) :401-406
[2]  
Crouzil A., 1996, Proceedings of the 13th International Conference on Pattern Recognition, P632, DOI 10.1109/ICPR.1996.546101
[3]   Local stereo matching with adaptive support-weight, rank transform and disparity calibration [J].
Gu, Zheng ;
Su, Xianyu ;
Liu, Yuankun ;
Zhang, Qican .
PATTERN RECOGNITION LETTERS, 2008, 29 (09) :1230-1235
[4]  
Hirschmuller H., 2007, IEEE COMP C COMP VIS
[5]   A STEREO MATCHING ALGORITHM WITH AN ADAPTIVE WINDOW - THEORY AND EXPERIMENT [J].
KANADE, T ;
OKUTOMI, M .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1994, 16 (09) :920-932
[6]  
Konolige K., 1997, P 8 INT S ROBOTIC RE, P203, DOI DOI 10.1007/978-1-4471-1580-9_19
[7]  
Mattoccia S., 2009, AS C COMP VIS, V11, P371
[8]  
Richardt C, 2010, LECT NOTES COMPUT SC, V6313, P510
[9]   A taxonomy and evaluation of dense two-frame stereo correspondence algorithms [J].
Scharstein, D ;
Szeliski, R .
INTERNATIONAL JOURNAL OF COMPUTER VISION, 2002, 47 (1-3) :7-42
[10]  
Scharstein D, 2003, PROC CVPR IEEE, P195