Real-Time Stereo Using Foreground Segmentation and Hierarchical Disparity Estimation

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.