基于灰度段的立体匹配算法
作者:
基金项目:

高等学校骨干教师资助计划资助项目


A Stereo Matching Algorithm Based on Gray-Level Segments
  • 摘要
  • | |
  • 访问统计
  • |
  • 参考文献 [15]
  • |
  • 相似文献
  • |
  • 引证文献
  • | |
  • 文章评论
    摘要:

    立体匹配一直是计算机视觉领域的一个中心研究问题.为了得到适用于IBR(image-basedrendering)技术中视图合成的比较精确的高密度视差图,提出了一种基于灰度段的立体匹配算法.该算法以灰度段作为匹配基元,并将应用于语音识别的DTW(dynamictimewarping)方法引入灰度段的匹配算法中.相对于点基元,灰度段基元覆盖的图像空间要大得多,且不易受噪声、光度变化等因素的影响,因此可以减少误匹配发生的几率,更容易进行匹配,比特征线段、二次曲线等匹配基元计算要简便得多.实验结果表明,该算法效果良好,具有实用价值.

    Abstract:

    Stereo matching has long been one of the central research problems in computer vision. A stereo matching algorithm is proposed based on gray level segments in order to recover dense depth map for the application of view synthesis in IBR (image-based rendering). This algorithm uses gray level segments as elements to be matched, and introduces the principle of DTW (dynamic time warping), which applied for speech recognition, into the matching processes on the segments. Covering more image space than point elements, gray-level segments are less sensitive to noise and photometric variations and easier to be matched, and can reduce the false matching. Moreover, gray-level segments segments require less computational resources than feature-based line segments and conices. Experimental results show that this algorithm is effective and of great value to use.

    参考文献
    [1] Grimson, W.E.L. Computational experiments with a feature based stereo algorithm. IEEE Transactions on PAMI, 1985,7(1):17~34.
    [2] Terzopoulos, D. The computation of visible surface representation. IEEE Transactions on PAMI, 1988,10(4):417~438.
    [3] Baker, H.H., Binford, T.O. Depth from edge and intensity based stereo. In: Proceedings of the 7th Joint Conference on Artificial Intelligence. 1981. 631~636.
    [4] Hoff, W., Ahuja, N. Surfaces from stereo: integrating feature matching, disparity estimation, and contour detection. IEEE Transactions on PAMI, 1989,11(2):121~136.
    [5] Ohta, Y., Kanade, T. Stereo by intra- and inter-scanline search using dynamic programming. IEEE Transactions on PAMI, 1985,7(2):139~154.
    [6] Lan, Zhong-dan, Roger, M. Robust matching by partial correlation. Technical Report, 2643, INRIA, 1995.
    [7] Cochran, S., Medioni, G. 3-D surface description from binocular stereo. IEEE Transactions on PAMI, 1992,14(10):981~994.
    [8] Sun, Chang-ming. A fast stereo matching method. In: Proceedings of Digital Image and Vision Computing: Techniques and Applications. Auckland, New Zealand: Massey University, 1997. 95~100. http://www.cmis.csiro.au/IAP/RecentProjects/StereoEE02.htm.
    [9] Sun, Chang-ming. Multi-Resolution stereo matching using maximum-surface techniques. In: Proceedings of Digital Image and Vision Computing: Techniques and Applications. 1999. 195~200. http://www.cmis.csiro.au/IAP/RecentProjects/StereoEEO2.htm.
    [10] Faugeras, O., Hotz, B., Mathieu, H., et al. Real time correlation-based stereo: algorithm, implementation and applications. Technical Report, 2013, INRIA, 1993.
    [11] Frhlinghaus, T., Buhmann, J.M. Regularizing phase-based stereo. In: Proceedings of the International Conference on Pattern Recognition (ICPR'96). 1996. 451~455. http://www-dbv.informatik.uni-bonn.de/abstracts/friehlinghaus.icpr06.html.
    [12] Crespi, B., Alex, G. Cozzi, analog computation for phase-based disparity estimation: continuous and discrete models. Machine Vision and Applications, 1998,11(2):83~95.
    [13] Zhou, Dong-xiang, Cai, Xuan-ping, Sun, Mao-yin. A feature-constrained stereo matching algorithm. In: Proceedings of the 6th International Conference of CAD/CG'99. Shanghai: Wen Hui Publishers, 1999.
    [14] Li, L., Ma, S.D. 3D pose estimation from a N-degree planar curve in two perspective views. In: Proceedings of the 13th ICPR. 1996. http://www.cs.cornell.edu/Lili/publications.html.
    [15] Rabiner, L.R., Schafter, R.W. Digital Processing of Speech Signals. Englewood Cliffs, NJ: Prentice Hall, Inc., 1978.
    相似文献
    网友评论
    网友评论
    分享到微博
    发 布
引用本文

周东翔,蔡宣平,孙茂印.基于灰度段的立体匹配算法.软件学报,2001,12(7):1101-1106

复制
分享
文章指标
  • 点击次数:4023
  • 下载次数: 5154
  • HTML阅读次数: 0
  • 引用次数: 0
历史
  • 收稿日期:1999-11-30
  • 最后修改日期:2000-12-05
文章二维码
您是第19867784位访问者
版权所有:中国科学院软件研究所 京ICP备05046678号-3
地址:北京市海淀区中关村南四街4号,邮政编码:100190
电话:010-62562563 传真:010-62562533 Email:jos@iscas.ac.cn
技术支持:北京勤云科技发展有限公司

京公网安备 11040202500063号