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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Utsumi, Y. Iwai, Y. Yachida, M. |
| Copyright Year | 2009 |
| Abstract | Probabilistic and statistical model analysis methods based on the Bayesian approach have recently been applied to face tracking. Here, we propose a face tracking method based on a Bayesian framework of image sequences. We assume that an observed space is three-dimensional (3D) and model facial shape, rotation and translation in 3D. A 3D positional hypothesis is generated using the facial translation model. The likelihood of facial existence is calculated from the output of the classifier learned using the AdaBoost M1algorithm. The results of an experiment show the efficiency of the proposed method for face tracking. |
| Starting Page | 265 |
| Ending Page | 269 |
| File Size | 1813200 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781424433353 |
| DOI | 10.1109/ICAPR.2009.32 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-02-04 |
| Publisher Place | India |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Histograms Shape Statistical analysis Bayesian methods Face recognition Particle filters Pattern recognition Image sequences Face detection Pattern analysis |
| Content Type | Text |
| Resource Type | Article |
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