DocumentCode :
3016916
Title :
Polarization and Phase-Shifting for 3D Scanning of Translucent Objects
Author :
Chen, Tongbo ; Lensch, Hendrik P A ; Fuchs, Christian ; Seidel, Hans-Peter
Author_Institution :
Max-Planck-Inst. fur Inf., Saarbrucken
fYear :
2007
fDate :
17-22 June 2007
Firstpage :
1
Lastpage :
8
Abstract :
Translucent objects pose a difficult problem for traditional structured light 3D scanning techniques. Subsurface scattering corrupts the range estimation in two ways: by drastically reducing the signal-to-noise ratio and by shifting the intensity peak beneath the surface to a point which does not coincide with the point of incidence. In this paper we analyze and compare two descattering methods in order to obtain reliable 3D coordinates for translucent objects. By using polarization-difference imaging, subsurface scattering can be filtered out because multiple scattering randomizes the polarization direction of light while the surface reflectance partially keeps the polarization direction of the illumination. The descattered reflectance can be used for reliable 3D reconstruction using traditional optical 3D scanning techniques, such as structured light. Phase-shifting is another effective descattering technique if the frequency of the projected pattern is sufficiently high. We demonstrate the performance of these two techniques and the combination of them on scanning real-world translucent objects.
Keywords :
computational geometry; image reconstruction; image resolution; light polarisation; light scattering; optical scanners; 3D translucent object geometry; image resolution; optical 3D scanning phase-shifting; optical 3D scanning polarization; polarization-difference imaging; reliable 3D reconstruction; signal-to-noise ratio; subsurface scattering; surface reflectance; Image reconstruction; Light scattering; Lighting; Optical filters; Optical imaging; Optical polarization; Optical scattering; Reflectivity; Signal to noise ratio; Surface reconstruction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition, 2007. CVPR '07. IEEE Conference on
Conference_Location :
Minneapolis, MN
ISSN :
1063-6919
Print_ISBN :
1-4244-1179-3
Electronic_ISBN :
1063-6919
Type :
conf
DOI :
10.1109/CVPR.2007.383209
Filename :
4270234
Link To Document :
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