Abstract
This paper presents an algorithm for the real-time computation of disparity using video stereo images captured by a stereo webcam. This algorithm is designed to provide both real-time throughput and robust disparity estimation for real-world applications where computation is limited to a pre-defined region-of-interest (ROI). More specifically, this algorithm is used as part of a hand-pair gesture recognition application where the disparity is computed for two ROI around a hand-pair identified by the segmentation component of the recognition application. The developed algorithm provides the required relative difference in disparity with background at high frame rates for the hand-pair gesture recognition application. The results obtained with an inexpensive commercial VGA stereo webcam show a robust disparity computation of 20 ms/frame enabling real-time hand-pair gesture recognition at 25 fps with >90% recognition rate for a maximum hand speed of 40 cm/s and for hand distances between 30 and 150 cm away from the camera.
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