[1] Bleyer M, Breiteneder C. Stereo matching—state-of-the-art and research challenges[M]. Advanced topics in computer vision. London: Springer, 143-179(2013).

[2] Scharstein D, Szeliski R. A taxonomy and evaluation of dense two-frame stereo correspondence algorithms[J]. International Journal of Computer Vision, 47, 7-42(2002). http://doi.ieeecomputersociety.org/10.1109/SMBV.2001.988771

[3] Sun J, Zheng N N, Shum H Y. Stereo matching using belief propagation[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 25, 787-800(2003). http://dl.acm.org/citation.cfm?id=859018

[4] Boykov Y, Veksler O, Zabih R. Fast approximate energy minimization via graph cuts[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 23, 1222-1239(2001). http://dl.acm.org/citation.cfm?id=505473&preflayout=flat

[5] Bleyer M, Gelautz M. Simple buteffective tree structures for dynamic programming-based stereo matching. [C]∥International Conference on Computer Vision Theory and Applications, Funchal, Portugal, 415-422(2008).

[6] Zhu S P, Li Z. A stereo matching algorithm using improved gradient and adaptive window[J]. Acta Optica Sinica, 35, 0110003(2015).

[7] Yoon K J, Kweon I S. Adaptive support-weight approach for correspondence search[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 28, 650-656(2006). http://dl.acm.org/citation.cfm?id=1115788

[8] Hosni A, Rhemann C, Bleyer M et al. Fast cost-volume filtering for visual correspondence and beyond[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 35, 504-511(2013). http://ieeexplore.ieee.org/document/6256668/

[9] Cigla C. Recursive edge-aware filters for stereo matching. [C]∥Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 27-34(2015).

[10] Yang Q, Li D, Wang L et al. Full-image guided filtering for fast stereo matching[J]. IEEE Signal Processing Letters, 20, 237-240(2013). http://ieeexplore.ieee.org/document/6416925/

[11] Yang Q. Local smoothness enforced cost volume regularization for fast stereo correspondence[J]. IEEE Signal Processing Letters, 22, 1429-1433(2015). http://ieeexplore.ieee.org/document/7055282/

[12] Yang Q. A non-local cost aggregation method for stereo matching. [C]∥IEEE Conference on Computer Vision and Pattern Recognition, 1402-1409(2012).

[13] Mei X, Sun X, Dong W M et al. Segment-tree based cost aggregation for stereo matching. [C]∥Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 313-320(2013).

[14] Yao P, Zhang H, Xue Y et al. Segment-tree based cost aggregation for stereo matching with enhanced segmentation advantage. [C]∥IEEE International Conference on Acoustics, Speech and Signal Processing, 2027-2031(2017).

[15] Ma Z Y, He K M, Wei Y C et al. Constant time weighted median filtering for stereo matching and beyond. [C]∥Proceedings of the IEEE International Conference on Computer Vision, 49-56(2013).

[16] Sun X, Mei X, Jiao S H et al. Stereo matching with reliable disparity propagation. [C]∥IEEE International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission, 132-139(2011).

[17] Zhang K, Fang Y, Min D et al. Cross-scale cost aggregation for stereo matching. [C]∥Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 1590-1597(2014).