Real-time disparity estimation using foreground segmentation for stereo sequences

We propose a fast disparity estimation algorithm using background registration and object segmentation for stereo sequences from fixed cameras. Dense background disparity information i 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 interframe 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/s for x 320 × 240 stereo sequences on an ordinary PC.