[1] |
Scharstein D, Szeliski R. A taxonomy and evaluation of densetwo-frame stereo correspondence algorithms [J]. InternationalJournal of Computer Vision, 2002, 47(1/2/3): 7-42. |
[2] |
|
[3] |
|
[4] |
Yoon K J, Kweon I S. Adaptive support weight approach forcorrespondence search [J]. IEEE Transactions on PatternAnalysis and Machine Intelligence, 2006, 28(4): 650-656. |
[5] |
|
[6] |
Sun J, Zheng N N, Shum H Y. Stereo matching using beliefpropagation [J]. IEEE Transactions on Pattern Analysis andMachine Intelligence, 2003, 25(7): 787-800. |
[7] |
|
[8] |
Tao H, Sawhney H S, Kumar R. A global matchingframework for stereo computation [C]//ProceedingsInternational Conference on Computer Vision IEEE, 2001:532-539. |
[9] |
Comaniciu D, Meer P. Mean shift: a robust approach towardfeature space analysis [J]. IEEE Transactions on PatternAnalysis and Machine Intelligence, 2002, 24(5): 603-619. |
[10] |
|
[11] |
|
[12] |
Chi Linghong. Research and application on stereo matching[D]. Hefei: University of Science and Technology of China,2011. (in Chinese) |
[13] |
Yang Q, Wang L, Yang R, et al. Real-time global stereomatching using hierarchical belief propagation [C]//BMVC,2006. |
[14] |
|
[15] |
Shi C, Wang G, Pei X, et al. High-accuracy stereo matchingbased on adaptive ground control points [C]//Submitted toIEEE TIP, 2012. |
[16] |
|
[17] |
|
[18] |
Wang Zengfu, Zheng Zhigang. A region based stereomatching algorithm using cooperative optimization [C]//Proceedings of the 2008 IEEE Computer Society Conferenceon Computer Vision and Pattern Recognition, 2008: 1-8. |
[19] |
Tombari F, Mattoccia S, Stefano L D. Segmentation basedadaptive support for accurate stereo correspondence[C]//IEEEPacific Rim Symposium on Video and Technology, 2007:427-438. |