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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Li Zhang Nejati, H. Foo, L. Keng Teck Ma Dong Guo Sim, T. |
| Copyright Year | 2013 |
| Description | Author affiliation: Sch. of Comput., Nat. Univ. of Singapore, Singapore, Singapore (Li Zhang; Nejati, H.; Foo, L.; Keng Teck Ma; Sim, T.) || Facebook Inc., Palo Alto, CA, USA (Dong Guo) |
| Abstract | Identical twins pose a great challenge to face recognition due to high similarities in their appearances. Motivated by the psychological findings that facial motion contains identity signatures and the observation that twins may look alike but behave differently, we develop a talking profile to use the identity signatures in the facial motion to distinguish between identical twins. The talking profile for a subject is defined as a collection of multiple types of usual face motions from the video. Given two talking profiles, we compute the similarities of all same type of face motion in both profiles and then perform the classification based on those similarities. Our approach, named Exceptional Motion Reporting Model (EMRM), is unrelated with appearance, and can handle realistic facial motion in human subjects, with no restrictions of speed of motion, or video frame rate. The experimental results on a video database containing 39 pairs of twins demonstrate that identical twins can be distinguished by their talking profiles. Moreover, we also apply our approach on non-twin population on a moderate YouTube dataset, with results verifying that the talking profile can be the potential biometric. |
| Sponsorship | IEEE Biomet. Counc. |
| Starting Page | 1 |
| Ending Page | 6 |
| File Size | 2226901 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781467355452 |
| e-ISBN | 9781467355469 |
| e-ISBN | 9781467355445 |
| DOI | 10.1109/FG.2013.6553700 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2013-04-22 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Face Face recognition Databases Accuracy Probes Psychology Statistics |
| Content Type | Text |
| Resource Type | Article |
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