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Real-Time Stereo Using Foreground Segmentation and Hierarchical Disparity Estimation

  • Hansung Kim
  • Dong Bo Min
  • Kwanghoon Sohn
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3767)

Abstract

We propose a fast disparity estimation algorithm using background registration and object segmentation for stereo sequences from fixed cameras. Dense background disparity information is calculated in an initialization step so that only disparities of moving object regions are updated in the main process. We propose a real-time segmentation technique using background subtraction and inter-frame differences, and a hierarchical disparity estimation using a region-dividing technique and shape-adaptive matching windows. Experimental results show that the proposed algorithm provides accurate disparity vector fields with an average processing speed of 15 frames/sec for 320x240 stereo sequences on a common PC.

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References

  1. 1.
    Scharstein, D., Szeliski, R.: A Taxonomy and Evaluation of Dense Two-frame Stereo Correspondence Algorithms. IJCV 47, 7–42 (2002)zbMATHCrossRefGoogle Scholar
  2. 2.
  3. 3.
    Schreer, O., Brandenburg, N., Kauff, P.: Real-time Disparity Analysis for Applications in Immersive Teleconference Scenarios - a Comparative Study. In: Proc. ICIAP, pp. 346–351 (2001)Google Scholar
  4. 4.
    Forstmann, S., Ohya, J., Kanou, Y., Schmitt, A., Thuering, S.: Real-time Stereo by Using Dynamic Programming. In: Proc. CVPR, p. 29 (2004)Google Scholar
  5. 5.
    Muhlmann, K., Maier, D., Hesser, J., Manner, R.: Calculating Dense Disparity Maps from Color Stereo Images, an Efficient Implementation. IJCV 47, 79–88 (2002)CrossRefGoogle Scholar
  6. 6.
    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
  7. 7.
  8. 8.
    Kim, H., Kitahara, I., Kogure, K., Hagita, N., Sohn, K.: Sat-Cam: Personal Satellite Virtual Camera. Proc. PCM 3, 87–94 (2004)Google Scholar
  9. 9.
    Kumar, P., Sengupta, K., Ranganath, S.: Real Time Detection and Recognition of Human Profiles using Inexpensive Desktop Cameras. Proc. ICPR 1, 1096–1099 (2000)Google Scholar
  10. 10.
    Zitnick, L., Kanade, T.: A Cooperative Algorithm for Stereo Matching and Occlusion Detection. IEEE Trans. PAMI 22(7), 675–684 (2000)Google Scholar
  11. 11.
    Hirschmuller, H.: Improvements in Real-time Correlation-based Stereo Vision. In: Proc. CVPR Stereo Workshop, pp. 141–148 (2001)Google Scholar
  12. 12.
    Sun, C.: Fast Stereo Matching Using Rectangular Subregioning and 3D Maximum-surface Techniques. IJCV 42(1), 7–42 (2002)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Hansung Kim
    • 1
  • Dong Bo Min
    • 1
  • Kwanghoon Sohn
    • 1
  1. 1.Dept. of Electrical and Electronics Eng.Yonsei UniversitySeoulKorea

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