Fast Dense Stereo Matching Using Adaptive Window in Hierarchical Framework

  • SangUn Yoon
  • Dongbo Min
  • Kwanghoon Sohn
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4292)


A new area-based stereo matching in hierarchical framework is proposed. Local methods generally measure the similarity between the image pixels using local support window. An appropriate support window, where the pixels have similar disparity, should be selected adaptively for each pixel. Our algorithm consists of the following two steps. In the first step, given an estimated initial disparity map, we obtain an object boundary map for distinction of homogeneous/object boundary region. It is based on the assumption that the depth boundary exists inside of intensity boundary. In the second step for improving accuracy, we choose the size and shape of window using boundary information to acquire the accurate disparity map. Generally, the boundary regions are determined by the disparity information, which should be estimated. Therefore, we propose a hierarchical structure for simultaneous boundary and disparity estimation. Finally, we propose post-processing scheme for removal of outliers. The algorithm does not use a complicate optimization. Instead, it concentrates on the estimation of a optimal window for each pixel in improved hierarchical framework, therefore, it is very efficient in computational complexity. The experimental results on the standard data set demonstrate that the proposed method achieves better performance than the conventional methods in homogeneous regions and object boundaries.


Object Boundary Stereo Match Optimal Window Hierarchical Framework Disparity Estimation 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Scharstein, D., Szeliski, R.: A taxonomy and evaluation of dense two-frame stereo correspondence algorithms. IJCV 47, 7–42 (2002)MATHCrossRefGoogle Scholar
  2. 2.
    Kanade, T., Okutomi, M.: A Stereo Matching Algorithm with an Adaptive Window: Theory and Experiments. PAMI 16(9), 920–932 (1994)Google Scholar
  3. 3.
    Boykov, Y., Veksler, O., Zabih, R.: A Variable Window Approach to Early Vision. PAMI 20(12), 1283–1294 (1998)Google Scholar
  4. 4.
    Veksler, O.: Fast Variable Window for Stereo Correspondence using Integral Images. CVPR 1, 556–561 (2003)Google Scholar
  5. 5.
    Fusiello, A., Roberto, V., Trucco, E.: Efficient Stereo with Multiple Windowing. CVPR, 858–863 (1997)Google Scholar
  6. 6.
    Bobick, A.F., Intille, S.S.: Large Occlusion Stereo. IJCV 33(3), 181–200 (1999)CrossRefGoogle Scholar
  7. 7.
    Kang, S.B., Szeliski, R., Jinxjang, C.: Handling Occlusions in Dense Multi-View Stereo. CVPR 1, 103–110 (2001)Google Scholar
  8. 8.
    Veksler, O.: Stereo matching by compact windows via minimum ratio cycle. In: ICCV 2001, pp. 540–547 (2001)Google Scholar
  9. 9.
    Kim, H., Choe, Y., Sohn, K.: Disparity estimation using region-dividing technique with energy-based regularization. Optical Engineering 43(8), 1882–1890 (2004)CrossRefGoogle Scholar
  10. 10.
    Yoon, K.-J., Kweon, I.-S.: Locally Adaptive Support- Weight Approach for Visual Correspondence Search. CVPR 2, 924–931 (2005)Google Scholar
  11. 11.
    Boykov, Y., Veksler, O., Zabih, R.: Fast approximate energy minimization via graph cut. PAM 23, 1222–1239 (2001)Google Scholar
  12. 12.
    Kolmogorov, V., Zabih, R.: Computing visual correspondence with occlusions using graph cuts. In: ICCV 2001, pp. 508–515 (2001)Google Scholar
  13. 13.
    Kim, Y., Lee, J.H., Park, C., Sohn, K.: MPEG-4 compatible stereoscopic sequence CODEC for stereo broadcasting. IEEE Trans. on Consumer Electronics 51(4), 1227–1236 (2005)CrossRefGoogle Scholar
  14. 14.
    Veksler, O.: Stereo correspondence by dynamic programming on a tree. CVPR 2, 20–25 (2005)Google Scholar
  15. 15.
    Muhlmann, K., Maier, D., Hesser, J., Manner, R.: Calculating dense disparity maps from color stereo images, an efficient implementation. SMBV, 30–36 (2001)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • SangUn Yoon
    • 1
  • Dongbo Min
    • 1
  • Kwanghoon Sohn
    • 1
  1. 1.Dept. of Electrical and Electronic Eng.Yonsei UniversitySeoulKorea

Personalised recommendations