• Acta Optica Sinica
  • Vol. 38, Issue 1, 0115004 (2018)
Jie Liu*, Jianxun Zhang, Yu Dai, and He Su
Author Affiliations
  • Institute of Robotics & Automatic Information System, Nankai University Tianjin 300071, China
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    DOI: 10.3788/AOS201838.0115004 Cite this Article Set citation alerts
    Jie Liu, Jianxun Zhang, Yu Dai, He Su. Dense Stereo Matching Based on Cross-Scale Guided Image Filtering[J]. Acta Optica Sinica, 2018, 38(1): 0115004 Copy Citation Text show less
    References

    [1] Scharstein D, Szeliski R, Zabih R. A taxonomy and evaluation of dense two-frame stereo correspondence algorithms[C]. IEEE Stereo and Multi-Baseline Vision, 47, 7-42(2002).

    [2] Bleyer M, Gelautz M. Graph-cut-based stereo matching using image segmentation with symmetrical treatment of occlusions[J]. Signal Processing: Image Communication, 22, 127-143(2007). http://dl.acm.org/citation.cfm?id=1231656

    [3] Kim J C, Lee K M, Choi B T. A dense stereo matching using two-pass dynamic programming with generalized ground control points[C]. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2, 1075-1082(2005).

    [4] Luo W J, Schwing A G, Urtasun R. Efficient deep learning for stereo matching[C]. IEEE Conference on Computer Vision and Pattern Recognition, 5695-5703(2016).

    [5] Žbontar J. LeCun Y. Stereo matching by training a convolutional neural network to compare image patches[J]. The Journal of Machine Learning Research, 17, 2287-2318(2016). http://dl.acm.org/citation.cfm?id=2946710

    [6] Kanade T, Okutomi M. A stereo matching algorithm with an adaptive window: Theory and experiment[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 16, 920-932(1994).

    [7] Yoon K J, Kweon 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] Shi H, Zhu H, Wang J et al. Segment-based adaptive window and multi-feature fusion for stereo matching[J]. Journal of Algorithms and Computational Technology, 10, 184-200(2016). http://www.researchgate.net/publication/293041801_Segment-based_adaptive_window_and_multi-feature_fusion_for_stereo_matching

    [9] Yang Q X. Stereo matching using tree filtering[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 37, 834-846(2015). http://ieeexplore.ieee.org/xpls/icp.jsp?arnumber=6888475

    [10] Rhemann C, Hosni A, Bleyer M et al. Fast cost-volume filtering for visual correspondence and beyond[C]. IEEE Conference on Computer Vision and Pattern Recognition, 3017-3024(2011).

    [11] He K M, Sun J, Tang X O. Guided image filtering[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 35, 1397-1409(2013).

    [12] Zhang K, Fang Y Q, Min D B et al. Cross-scale cost aggregation for stereo matching[J]. IEEE Conference on Transactions on Circuits and Systems for Video Technology, 27, 965-976(2017). http://dl.acm.org/citation.cfm?id=2679600.2680113

    [13] Zhu S P, Yan L N, Li Z. Stereo matching algorithm based on improved Census transform and dynamic.

    [14] Crow F C. Summed-area tables for texture mapping[C]. ACM Conference on Computer Graphics and Interactive Techniques, 207-212(1984).

    [15] Pires B R, Singh K. Moura J M F. Approximating image filters with box filters[C]. IEEE International Conference on Image Processing, 85-88(2011).

    [16] Comaniciu D, Meer P. Mean shift: A robust approach toward feature space analysis[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24, 603-619(2002). http://bioinformatics.oxfordjournals.org/external-ref?access_num=10.1109/34.1000236&link_type=DOI

    [17] Liu J, Zhang J X, Dai Y. Dense stereo matching based on region growing[J]. Robot, 39, 182-188(2017).

    [18] Milanfar P. A tour of modern image filtering: New insights and methods, both practical and theoretical[J]. IEEE Signal Processing Magazine, 30, 106-128(2013). http://amstat.tandfonline.com/servlet/linkout?suffix=cit0022&dbid=16&doi=10.1080%2F10618600.2015.1048345&key=10.1109%2FMSP.2011.2179329

    [20] Zhang K, Lu J B, Lafruit G. Cross-based local stereo matching using orthogonal integral images[J]. IEEE Transactions on Circuits and Systems for Video Technology, 19, 1073-1079(2009). http://dl.acm.org/citation.cfm?id=1641709

    [21] Wang L, Yang R G. Global stereo matching leveraged by sparse ground control points[C]. IEEE Conference on Computer Vision and Pattern Recognition, 3033-3040(2011).

    CLP Journals

    [1] Jinsheng Xiao, Hong Tian, Wentao Zou, Le Tong, Junfeng Lei. Stereo Matching Based on Convolutional Neural Network[J]. Acta Optica Sinica, 2018, 38(8): 0815017

    [2] Yi Zhang, Zhiyu Xiang, Shuya Chen, Shuxia Gu. Optimization on Visual Odometry under Weak Texture Environment[J]. Acta Optica Sinica, 2018, 38(6): 0615001

    Jie Liu, Jianxun Zhang, Yu Dai, He Su. Dense Stereo Matching Based on Cross-Scale Guided Image Filtering[J]. Acta Optica Sinica, 2018, 38(1): 0115004
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