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A Study on the Generation and Processing of Depth Map for Multi-resolution Image Using Belief Propagation Algorithm
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 Title & Authors
A Study on the Generation and Processing of Depth Map for Multi-resolution Image Using Belief Propagation Algorithm
Jee, Innho;
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 Abstract
3D image must have depth image for depth information in order for 3D realistic media broadcasting. We used generally belief propagation algorithm to solve probability model. Belief propagation algorithm is operated by message passing between nodes corresponding to each pixel. The high resolution image will be able to precisely represent but that required much computational complexity for 3D representation. We proposed fast stereo matching algorithm using belief propagation with multi-resolution based wavelet or lifting. This method can be shown efficiently computational time at much iterations for accurate disparity map.
 Keywords
Belief Propagation;Stereo;Disparity Map;Multi-resolution;
 Language
Korean
 Cited by
 References
1.
J. Sun, H-Y Shum, and N. Zheng, "Stereo matching using Belief Propagation," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 25, No. 7, pp. 1261-1268, July 2003.

2.
Won-ill Kim, "A study on the smoothing method for efficient video stream transmission on IPTV network," International Journal of the Institute of Internet, Broadcasting and Communication(IIIBC) vol.3, No. 2, pp.16-25, 2011.

3.
S. Jang and Innho Jee, "A study on fast stero matching algorithm using Belief Propagation in multi-resolution domain," Journal of The Institute of Internet, Broadcasting and Communication (JIIBC) No, 4, pp. 67-73, Aug. 2008.

4.
Y. Boyko, O. Veksler and R. Zabih, "Fast approximate energy minimization via graph cuts," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 23, No. 11, pp. 1222-1239, 2001. crossref(new window)

5.
C. Sun, "Multi-resolution stereo matching using maximum-surface techniques," in Digital Image Computing: Techniques and Applications. pp. 195-200, Dec. 1999.

6.
I. J. Cox, S. L. Hingorani, S, B. Rao, and B. M. Maggs, "A maximum likelihood stereo algorithm," Computer Vision and Pattern Recognition, 1997.

7.
R. Szeliski, R. Zabih, D. Scharstein, O. Veksler, V. Kolmogorov, A. Agarwala, M. Tappen, and C. Rother, "A comparative study of energy minimization methods for markov random fields with smoothness-base priors," IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 30, No. 6, pp. 1068-1080, June 2008. crossref(new window)