A Window-Based Adaptive Correspondence Search Algorithm Using Mean Shift and Disparity Estimation
Aiming at the problem of low efficiency and unsatisfactory matching of uniform texture regions in binocular stereo vision, we propose a rapid window-based adaptive correspondence search algorithm using mean shift and disparity estimation. Color aggregation is firstly carried out to the reference image and the target image through mean shift method in order to obtain images with low dynamic color range. Then we make disparity estimation to the pre-processed two images and compute disparities of uniform texture regions. Finally, adaptive window matching is completed and exact depth map is achieved through similarity computation and window-based support aggregation. Experimental results show that our algorithm is more efficient and keeps smooth disparity better than the prior window method.
Mean shift disparity estimation adaptive window matching binocular vision
Shujun Zhang Jianbo Zhang Yun Liu
College of Information Science & Technology Qingdao University of Science & Technology
国内会议
北京
英文
1-4
2011-11-04（万方平台首次上网日期，不代表论文的发表时间）