Using Dynamic Programming for Solving Variational Problems in Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
A fast algorithm for active contours and curvature estimation
CVGIP: Image Understanding
Depth Discontinuities by Pixel-to-Pixel Stereo
International Journal of Computer Vision
A Stereo Matching Algorithm with an Adaptive Window: Theory and Experiment
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Cooperative Algorithm for Stereo Matching and Occlusion Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Dense disparity estimation with a divide-and-conquer disparityspace image technique
IEEE Transactions on Multimedia
The MPEG-4 video standard verification model
IEEE Transactions on Circuits and Systems for Video Technology
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A new snake-based algorithm is presented to segment objects from a pair of stereo images. The proposed algorithm is built upon a new energy function defined in the disparity space in such a way to successfully locate the boundary of an object found in a stereo image pair. The distinction of our algorithm comes from its superb segmentation capability even when the objects in the image are occluded and the background behind them is cluttered. The computer simulation shows out-performing results over the well-known conventional snake algorithm in terms of segmentation accuracy.