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Content Provider | IEEE Xplore Digital Library |
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Author | Oxholm, G. Nishino, K. |
Copyright Year | 2014 |
Description | Author affiliation: Dept. of Comput., Drexel Univ., Philadelphia, PA, USA (Oxholm, G.; Nishino, K.) |
Abstract | The world is full of objects with complex reflectances, situated in complex illumination environments. Past work on full 3D geometry recovery, however, has tried to handle this complexity by framing it into simplistic models of reflectance (Lambetian, mirrored, or diffuse plus specular) or illumination (one or more point light sources). Though there has been some recent progress in directly utilizing such complexities for recovering a single view geometry, it is not clear how such single-view methods can be extended to reconstruct the full geometry. To this end, we derive a probabilistic geometry estimation method that fully exploits the rich signal embedded in complex appearance. Though each observation provides partial and unreliable information, we show how to estimate the reflectance responsible for the diverse appearance, and unite the orientation cues embedded in each observation to reconstruct the underlying geometry. We demonstrate the effectiveness of our method on synthetic and real-world objects. The results show that our method performs accurately across a wide range of real-world environments and reflectances that lies between the extremes that have been the focus of past work. |
Starting Page | 2163 |
Ending Page | 2170 |
File Size | 1178741 |
Page Count | 8 |
File Format | |
ISBN | 9781479951185 |
ISSN | 10636919 |
DOI | 10.1109/CVPR.2014.277 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2014-06-23 |
Publisher Place | USA |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Geometry Lighting Shape Estimation Three-dimensional displays Probabilistic logic Cameras |
Content Type | Text |
Resource Type | Article |
Subject | Computer Vision and Pattern Recognition Software |
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