DocumentCode :
2915706
Title :
Adequate reconstruction of transparent objects on a shoestring budget
Author :
Yeung, Sai-Kit ; Wu, Tai-Pang ; Tang, Chi-Keung ; Chan, Tony F. ; Osher, Stanley
Author_Institution :
Univ. of California, Los Angeles, CA, USA
fYear :
2011
fDate :
20-25 June 2011
Firstpage :
2513
Lastpage :
2520
Abstract :
Reconstructing transparent objects is a challenging problem. While producing reasonable results for quite complex objects, existing approaches require custom calibration or somewhat expensive labor to achieve high precision. On the other hand, when an overall shape preserving salient and fine details is sufficient, we show in this paper a significant step toward solving the problem on a shoestring budget, by using only a video camera, a moving spotlight, and a small chrome sphere. Specifically, the problem we address is to estimate the normal map of the exterior surface of a given solid transparent object, from which the surface depth can be integrated. Our technical contribution lies in relating this normal reconstruction problem to one of graph-cut segmentation. Unlike conventional formulations, however, our graph is dual-layered, since we can see a transparent object´s foreground as well as the background behind it. Quantitative and qualitative evaluation are performed to verify the efficacy of this practical solution.
Keywords :
calibration; graph theory; image reconstruction; image segmentation; video cameras; complex object; custom calibration; dual-layered graph; exterior surface map; graph-cut segmentation; moving spotlight; normal reconstruction problem; qualitative evaluation; quantitative evaluation; shoestring budget; small chrome sphere; solid transparent object adequate reconstruction; surface depth; video earner; Color;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on
Conference_Location :
Providence, RI
ISSN :
1063-6919
Print_ISBN :
978-1-4577-0394-2
Type :
conf
DOI :
10.1109/CVPR.2011.5995472
Filename :
5995472
Link To Document :
بازگشت