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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Binglong Xie Boult, T. Ramesh, V. Ying Zhu |
| Copyright Year | 2006 |
| Description | Author affiliation: Dept. of Real-Time Vision & Modeling, Siemens Corporate Res., Princeton, NJ (Binglong Xie) |
| Abstract | Automatic face recognition has a lot of application areas and current single-camera face recognition has severe limitations when the subject is not cooperative, or there are pose changes and different illumination conditions. A face recognition system using multiple cameras overcomes these limitations. In each channel, real-time component-based face detection detects the face with moderate pose and illumination changes employing fusion of individual component detectors for eyes and mouth, and the normalized face is recognized using an LDA recognizer. A reliability measure is trained using the features extracted from both face detection and recognition processes, to evaluate the inherent quality of channel recognition. The recognition from the most reliable channel is selected as the final recognition results. The recognition rate is far better than that of either single channel, and consistently better than common classifier fusion rules |
| Starting Page | 18 |
| Ending Page | 23 |
| File Size | 275038 |
| Page Count | 6 |
| File Format | |
| ISBN | 1424407443 |
| DOI | 10.1109/CIHSPS.2006.313294 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2006-10-16 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Face recognition Face detection Lighting Cameras Linear discriminant analysis Detectors Mouth Principal component analysis Road safety Eyes Reliability Measure Multi-Camera Face Recognition |
| Content Type | Text |
| Resource Type | Article |
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