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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Deng-Yuan Huang Wu-Chih Hu Mao-Hsiang Hsu |
| Copyright Year | 2009 |
| Abstract | In this paper, an adaptive skin color model switching based on AdaBoost method for face tracking is proposed. Possible skin clusters under illumination varying scenes are detected by an optimal skin color model, which is adaptively selected by a well-defined quality measure. The possible facial candidates are further validated by AdaBoost to determine whether human faces exist in video sequences or not. The tracking sequences reveal that good and robust results are obtained from dim- to profile- to back-light scenarios. The performance of the proposed method can achieve an average tracking time of about 145.4 ms/frame and a detection rate of 94.4%. |
| Starting Page | 326 |
| Ending Page | 329 |
| File Size | 417055 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424455430 |
| e-ISBN | 9781424455447 |
| DOI | 10.1109/ICICIC.2009.71 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-12-07 |
| Publisher Place | Taiwan |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Support vector machines Steganography Lighting Support vector machine classification Feature extraction Skin Wavelet packets Classification algorithms Cryptography Testing |
| Content Type | Text |
| Resource Type | Article |
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