• Acta Optica Sinica
  • Vol. 37, Issue 11, 1115004 (2017)
Xinjun Peng*, Jun Han, Yong Tang, Yuzhi Shang, and Yujin Yu
Author Affiliations
  • School of Communication and Information Engineering, Shanghai University, Shanghai 200444, China
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    DOI: 10.3788/AOS201737.1115004 Cite this Article Set citation alerts
    Xinjun Peng, Jun Han, Yong Tang, Yuzhi Shang, Yujin Yu. Anti-Noise Stereo Matching Algorithm Based on Improved Census Transform and Outlier Elimination[J]. Acta Optica Sinica, 2017, 37(11): 1115004 Copy Citation Text show less
    References

    [1] Scharstein D, Szeliski R. Ataxonomy and evaluation of dense two-frame stereo correspondence algorithms[J]. International Journal of Computer Vision, 47, 7-42(2002). http://ieeexplore.ieee.org/xpls/icp.jsp?arnumber=988771

    [2] Scharstein D, Szeliski R, Hirschmüller H[2017-05-31]. The middle stereo vision page [2017-05-31].http: ∥vision.middlebury.edu/stereo/..

    [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] Besse F, Rother C, Fitzgibbon A et al. PMBP: patchmatch belief propagation for correspondence field estimation[J]. International Journal of Computer Vision, 110, 2-13(2014). http://dl.acm.org/citation.cfm?id=2674555

    [5] Yang Q, Wang L, Yang R et al. Stereo matching with color-weighted correlation, hierarchical belief propagation, and occlusion handling[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 31, 492-504(2009). http://doi.ieeecomputersociety.org/10.1109/TPAMI.2008.99

    [6] Worby J, Maclean W J. Establishing visual correspondence from multi-resolution graph cuts for stereo-motion[C]. IEEE Fourth Canadian Conference on Computer and Robot Vision, 313-320(2007).

    [7] Gong Wenbiao, Gu Guohua, Qian Weixian et al. Stereo matching algorithm based on image sgmentation and adaptive support weight[J]. Acta Optica Sinica, 35, s210002(2015).

    [8] Mattoccia S, Giardino S, Gambini A. Accurate and efficient cost aggregation strategy for stereo correspondence based on approximated joint bilateral filtering[C]. Asian Conference on Computer Vision, 371-380(2009).

    [9] Zhang K, Lu J, 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://ieeexplore.ieee.org/document/4811952/

    [10] Mei X, Sun X, Zhou M et al. On building an accurate stereo matching system on graphics hardware[C]. IEEE International Conference on Computer Vision Workshops, 467-474(2011).

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

    [12] Hirschmuller H, Scharstein D. Evaluation of cost functions for stereo matching[C]. IEEE Conference on Computer Vision and Pattern Recognition, 1-8(2007).

    [13] Zabih R, Woodfill J. Non-parametric local transforms for computing visual correspondence[C]. European Conference on Computer Vision, 801, 151-158(1994).

    [14] Lim J, Kim Y, Lee S. A census transform-based robust stereo matching under radiometric changes[C]. Signal and Information Processing Association Annual Summit and Conference, 1-4(2016).

    [15] Chang N Y C, Tsai T H, Hsu B H et al. . Algorithm and architecture of disparity estimation with mini-census adaptive support weight[J]. IEEE Transactions on Circuits and Systems for Video Technology, 20, 792-805(2010). http://ieeexplore.ieee.org/document/5431623/

    [16] Wang Junzheng, Zhu Huajian, Li Jing. A census transform based stereo maching algorithm using variable support-weight[J]. Transactions of Beijing Institute of Technology, 33, 704-710(2013).

    [17] Zhu Shiping, Yan Lina, Li Zheng. Stereo matching algorithm based on improved census transform and dynamic programming[J]. Acta Optica Sinica, 36, 0415001(2016).

    [18] Hirschm H. Stereoprocessing by semiglobal matching and mutual information[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 30, 328-341(2008). http://ieeexplore.ieee.org/document/4359315/

    [19] Chang X, Zhou Z, Wang L et al. Real-time accurate stereo matching using modified two-pass aggregation and winner-take-all guided dynamic programming[C]. International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission, 73-79(2011).

    [20] Yang Q, Wang L, Yang R et al. Stereo matching with color-weighted correlation, hierachical belief propagation and occlusion handling[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 31, 2347-2354(2006). http://ieeexplore.ieee.org/xpls/icp.jsp?arnumber=1641041

    [21] Gales G, Crouzil A, Chambon S. A region-based randomized voting scheme for stereo matching[J]. Advances in Visual Computing, 182-191(2010).

    [22] Larsen E S, Mordohai P, Pollefeys M et al. Temporally consistent reconstruction from multiple video streams using enhanced belief propagation[C]. IEEE 11th International Conference on Computer Vision, 1-8(2007).

    [23] Humenberger M, Zinner C, Weber M et al. A fast stereo matching algorithm suitable for embedded real-time systems[J]. Computer Vision and Image Understanding, 114, 1180-1202(2010). http://www.sciencedirect.com/science/article/pii/S1077314210000895

    [24] Ma Li, Li Jingjiao, Ma Ji. Modified census transform with related information of neighborhood for stereo matching algorithm[J]. Computer Engineering and Applications, 50, 16-22(2014).

    CLP Journals

    [1] Yan Liu, Qingwu Li, Guanying Huo, Jun Xing. Local Binary Description Combined with Superpixel Segmentation Refinement for Stereo Matching[J]. Acta Optica Sinica, 2018, 38(6): 0615003

    Xinjun Peng, Jun Han, Yong Tang, Yuzhi Shang, Yujin Yu. Anti-Noise Stereo Matching Algorithm Based on Improved Census Transform and Outlier Elimination[J]. Acta Optica Sinica, 2017, 37(11): 1115004
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