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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Miao Liao Liang Wang Ruigang Yang Minglun Gong |
| Copyright Year | 2007 |
| Description | Author affiliation: Univ. of Kentucky, Lexington (Miao Liao; Liang Wang; Ruigang Yang) |
| Abstract | We present light fall-off stereo-LFS-a new method for computing depth from scenes beyond lambertian reflectance and texture. LFS takes a number of images from a stationary camera as the illumination source moves away from the scene. Based on the inverse square law for light intensity, the ratio images are directly related to scene depth from the perspective of the light source. Using this as the invariant, we developed both local and global methods for depth recovery. Compared to previous reconstruction methods for non-lamebrain scenes, LFS needs as few as two images, does not require calibrated camera or light sources, or reference objects in the scene. We demonstrated the effectiveness of LFS with a variety of real-world scenes. |
| Starting Page | 1 |
| Ending Page | 8 |
| File Size | 1249311 |
| Page Count | 8 |
| File Format | |
| ISBN | 1424411793 |
| ISSN | 10636919 |
| DOI | 10.1109/CVPR.2007.383159 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2007-06-17 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Layout Light sources Reflectivity Cameras Surface texture Stereo vision Lighting Reconstruction algorithms Computer vision Focusing |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Vision and Pattern Recognition Software |
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