Disparity Estimation for Objects of Interest

An algorithm for estimating the disparity of objects of interest is proposed. This algorithm uses image shifting and overlapping area to estimate the disparity value; thereby depth of the objects of interest can be obtained. The algorithm is able to perform at different levels of accuracy. However, as the accuracy increases the processing speed decreases. The algorithm is tested with static stereo images and sequence of stereo images. The experimental results are presented in this paper.




References:
[1] Kaufman, P.L., and Alm, A., Adler's Physiology of the Eye, Tenth
Edition, Elsevier Health Sciences, Nov 2002.
[2] Sekuler, R., Blake, R., Perception, Third Edition, McGraw-Hill, 1994.
[3] S. Birchfield and C. Tomasi, "Depth Discontinuities by Pixel-to-pixel
Stereo", International Journal of Computer Vision, Vol. 35 No. 3, pp.
269-293, 1999
[4] C.M. Sun, "Fast Stereo Matching using rectangular Subregioning and
3D Maximum-surface Techniques", International Journal of computer
Vision, Vol 47, 2002, pp 99-117
[5] L.D. Stefano, M. Marchionni, S. Mattoccia, "A Fast Area-based Stereo
Matching Algorithm", Image and Vision Computing, Elsevier, Vol 22,
2004, pp 983-1005.
[6] F. Tombari, S. Mattoccia, L.D. Stefano, "Segmentation-based Adaptive
Support for Accurate Stereo Correspondence", IEEE Pacific-Rim
Symposium on Image and Video Technology (PSIVT), 2007
[7] R.T. Collins, A.J. Lipton, T. Kanade, H. Fujiyoshi, D. Duggins, Y.
Tsin, D. Tolliver, N. Enomoto, and O. Hasegawa, "A System for
Video Surveillance and Monitoring: VSAM Final Report", Technical
report CMU-RI-TR-00-12, Robotics Institute, Carnegie Mellon
University, May 2000.