Physiological and Behavioral Lip Biometrics: A comprehensive study of their discriminative power
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| Title | Physiological and Behavioral Lip Biometrics: A comprehensive study of their discriminative power |
|---|---|
| Author | Wang, Shi-Lin; Liew, Alan Wee-Chung |
| Journal Name | Pattern Recognition |
| Year Published | 2012 |
| Place of publication | United Kingdom |
| Publisher | Elsevier |
| Abstract | Compared with other traditional biometric features such as face, finger print, or hand writing, lip biometric features contain both physiological and behavioral information. Physiologically, different people have different lips. On the other hand, people can usually be differentiated by their talking style. Current research on lip biometrics generally does not distinguish between the two kinds of information during feature extraction and classification and the interesting question of whether the physiological or the behavioral lip features are more discriminative has not been comprehensively studied. In this paper, different physiological and behavioral lip features are studied with respect to their discriminative power in speaker identification and verification. Our experimental results have shown that both the static lip texture feature and the dynamic shape deformation feature can achieve high identification accuracy (above 90%) and low verification error rate (below 5%). In addition, the lip rotation and centroid deformations, which are related to the speaker’s talking mannerism, are found to be useful for speaker identification and verification. In contrast to previous studies, our results show that behavioral lip features are more discriminative in speaker identification and verification compared to physiological features. |
| Peer Reviewed | Yes |
| Published | Yes |
| Alternative URI | http://dx.doi.org/10.1016/j.patcog.2012.02.016 |
| Volume | 45 |
| Issue Number | 9 |
| Page from | 3328 |
| Page to | 3335 |
| ISSN | 0031-3203 |
| Date Accessioned | 2012-06-20; 2012-11-20T23:51:23Z |
| Date Available | 2012-11-20T23:51:23Z |
| Research Centre | Institute for Integrated and Intelligent Systems |
| Faculty | Faculty of Science, Environment, Engineering and Technology |
| Subject | Computer Vision; Pattern Recognition and Data Mining |
| URI | http://hdl.handle.net/10072/47736 |
| Publication Type | Journal Articles (Refereed Article) |
| Publication Type Code | c1 |
Please use this identifier to cite this record: http://hdl.handle.net/10072/47736
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