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Photogeometric structured light: A self-calibrating and multi-viewpoint framework for accurate 3D modeling

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2 Author(s)
Daniel G. Aliaga ; Department of Computer Science, Purdue University, USA ; Yi Xu

Structured-light methods actively generate geometric correspondence data between projectors and cameras in order to facilitate robust 3D reconstruction. In this paper, we present photogeometric structured light whereby a standard structured light method is extended to include photometric methods. Photometric processing serves the double purpose of increasing the amount of recovered surface detail and of enabling the structured-light setup to be robustly self-calibrated. Further, our framework uses a photogeometric optimization that supports the simultaneous use of multiple cameras and projectors and yields a single and accurate multi-view 3D model which best complies with photometric and geometric data.

Published in:

Computer Vision and Pattern Recognition, 2008. CVPR 2008. IEEE Conference on

Date of Conference:

23-28 June 2008