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IEEE Transactions on Pattern Analysis and Machine Intelligence
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International Journal of Computer Vision
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International Journal of Computer Vision
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IEEE Computer Graphics and Applications
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CGI '96 Proceedings of the 1996 Conference on Computer Graphics International
Stereo Matching Using Belief Propagation
IEEE Transactions on Pattern Analysis and Machine Intelligence
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IEEE Transactions on Pattern Analysis and Machine Intelligence
Sub-Pixel Estimation Error Cancellation on Area-Based Matching
International Journal of Computer Vision
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IEEE Computer Graphics and Applications
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3DIM'99 Proceedings of the 2nd international conference on 3-D digital imaging and modeling
High-accuracy stereo depth maps using structured light
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Surfaces with occlusions from layered stereo
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Adaptive Census Transform: A novel hardware-oriented stereovision algorithm
Computer Vision and Image Understanding
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This paper presents a whole body surface imaging system based on stereo vision technology. We have adopted a compact and economical configuration which involves only four stereo units to image the frontal and rear sides of the body. The success of the system depends on a stereo matching process that can effectively segment the body from the background in addition to recovering sufficient geometric details. For this purpose, we have developed a novel sub-pixel, dense stereo matching algorithm which includes two major phases. In the first phase, the foreground is accurately segmented with the help of a predefined virtual interface in the disparity space image, and a coarse disparity map is generated with block matching. In the second phase, local least squares matching is performed in combination with global optimization within a regularization framework, so as to ensure both accuracy and reliability. Our experimental results show that the system can realistically capture smooth and complete whole body shapes with high accuracy.