DocumentCode :
2401425
Title :
Photogeometric structured light: A self-calibrating and multi-viewpoint framework for accurate 3D modeling
Author :
Aliaga, Daniel G. ; Xu, Yi
Author_Institution :
Dept. of Comput. Sci., Purdue Univ., West Lafayette, IN
fYear :
2008
fDate :
23-28 June 2008
Firstpage :
1
Lastpage :
8
Abstract :
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.
Keywords :
calibration; geometry; image reconstruction; solid modelling; 3D modeling; 3D reconstruction; cameras; multiviewpoint framework; photogeometric structured light; projectors; self-calibrating framework; Cameras; Computer science; Hardware; Image reconstruction; Photography; Photometry; Reflectivity; Robustness; Solid modeling; Surface reconstruction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition, 2008. CVPR 2008. IEEE Conference on
Conference_Location :
Anchorage, AK
ISSN :
1063-6919
Print_ISBN :
978-1-4244-2242-5
Electronic_ISBN :
1063-6919
Type :
conf
DOI :
10.1109/CVPR.2008.4587709
Filename :
4587709
Link To Document :
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