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| Title: | A Bayesian approach for shadow extraction from a single image |
| Authors: | Wu, Tai-Pang
Tang, Chi-Keung |
| Keywords: | Bayesian methods
Feature extraction
Image texture
Poisson equation |
| Issue Date: | Oct-2005 |
| Citation: | Proceedings 10th IEEE International Conference on Computer Vision, 17-21 October 2005, Beijing, China, part vol. 1, p. 480-487 |
| Abstract: | This paper addresses the problem of shadow extraction from a single image of a complex natural scene. No simplifying assumption on the camera and the light source other than the Lambertian assumption is used. Our method is unique because it is capable of translating very rough usersupplied hints into the effective likelihood and prior functions for our Bayesian optimization. The likelihood function requires a decent estimation of the shadowless image, which is obtained by solving the associated Poisson equation. Our Bayesian framework allows for the optimal extraction of smooth shadows while preserving texture appearance under the extracted shadow. Thus our technique can be applied to shadow removal, producing some best results to date compared with the current state-of-the-art techniques using a single input image. We propose related applications in shadow compositing and image repair using our Bayesian technique. |
| Rights: | © 2005 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. |
| URI: | http://hdl.handle.net/1783.1/2714 |
| Appears in Collections: | CSE Conference Papers
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| wushadow.pdf | pre-published version | 787Kb | Adobe PDF | View/Open |
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