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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Jian-Gang Wang Sung, E. Venkateswarlu, R. |
| Copyright Year | 2004 |
| Description | Author affiliation: Inst. for Infocomm Res., Singapore, Singapore (Jian-Gang Wang) |
| Abstract | A method is proposed to register visible and infrared face images. The vanishing-point based approach [J.G. Wang and E. Sung, 2001] is applied to the visible image to determine the 3D pose of the human head. Then the corresponding pose with respect to the infrared camera is computed through the known relationship by calibration between the visible and infrared cameras. By doing so, the skin temperature range within the infrared image can be superimposed over the visible face image. We use the EM strategy to first compute the 3D pose using some initially learned (PCA) model parameters, and then update iteratively the parameters for individual persons and their facial expressions till convergence. The EM technique models data uncertainty using Gaussian mixtures defined over positions and orientation of facial plane. The resulting weighted parameters estimation problem is solved using the Levenberg-Marquardt method. The results on the synthetic data and real images have verified the performance of the approach. |
| Sponsorship | IEEE Comput. Soc. Korea Inf. Sci. Soc. Korea Sci. Eng. Foundation Minstry of Inf. and Communications US Air Force Office of Sci. Res. WatchVision Inc |
| Starting Page | 638 |
| Ending Page | 644 |
| File Size | 1892025 |
| Page Count | 7 |
| File Format | |
| ISBN | 0769521223 |
| DOI | 10.1109/AFGR.2004.1301605 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2004-05-19 |
| Publisher Place | South Korea |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Infrared imaging Face recognition Cameras Registers Humans Head Optical computing Calibration Skin Temperature distribution |
| Content Type | Text |
| Resource Type | Article |
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