Normal Estimation of a Transparent Object Using a Video

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. When an overall shape preserving salient and fine details is sufficient, we...

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Bibliographic Details
Published in:IEEE transactions on pattern analysis and machine intelligence 2015-04, Vol.37 (4), p.890-897
Main Authors: Sai-Kit Yeung, Tai-Pang Wu, Chi-Keung Tang, Chan, Tony F., Osher, Stanley J.
Format: Article
Language:English
Subjects:
Cameras
Estimation
Image color analysis
Image segmentation
Optimization
Radiation detectors
Shape
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Summary: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. When an overall shape preserving salient and fine details is sufficient, we show in this paper a significant step toward solving the problem when the object's silhouette is available and simple user interaction is allowed, by using a video of a transparent object shot under varying illumination. Specifically, we 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 estimation 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.
ISSN:0162-8828
1939-3539
2160-9292
DOI:10.1109/TPAMI.2014.2346195