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Content Provider | IEEE Xplore Digital Library |
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Author | Breton, P. Zucker, S.W. |
Copyright Year | 1996 |
Description | Author affiliation: McGill Res. Centre for Intelligent Machines, McGill Univ., Montreal, Que., Canada (Breton, P.; Zucker, S.W.) |
Abstract | Many presume that parsing the shadows out of an image is a high-level task, because of the global nature of the shadow formation process. But shape-from-shading algorithms are low-level, in the sense that they seek solutions (surface normals or depth values) directly from image intensities. A dilemma arises: since shape-from-shading involves an illumination term, shadows must first be identified. We show that a structure intermediate between intensities and surfaces-the shading flow field-provides a solution to this dilemma. Our analysis is based on the observation that the geometric information that can be derived from images supports different inferences than the photometric information, and our specific goal will be to articulate this geometric structure and to show how shading flow fields can be reliably computed. |
Starting Page | 782 |
Ending Page | 789 |
File Size | 784194 |
Page Count | 8 |
File Format | |
ISBN | 0818672595 |
ISSN | 10636919 |
DOI | 10.1109/CVPR.1996.517161 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 1998-06-18 |
Publisher Place | USA |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Surface reconstruction Lighting Layout Image analysis Photometry Light sources Shape Information analysis Robustness Computer vision |
Content Type | Text |
Resource Type | Article |
Subject | Computer Vision and Pattern Recognition Software |
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