Please use this identifier to cite or link to this item: https://doi.org/10.1109/WACV.2012.6163026
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dc.titleNew hope for recognizing twins by using facial motion
dc.contributor.authorZhang, L.
dc.contributor.authorYe, N.
dc.contributor.authorMarroquin, E.M.
dc.contributor.authorGuo, D.
dc.contributor.authorSim, T.
dc.date.accessioned2013-07-04T08:05:46Z
dc.date.available2013-07-04T08:05:46Z
dc.date.issued2012
dc.identifier.citationZhang, L.,Ye, N.,Marroquin, E.M.,Guo, D.,Sim, T. (2012). New hope for recognizing twins by using facial motion. Proceedings of IEEE Workshop on Applications of Computer Vision : 209-214. ScholarBank@NUS Repository. <a href="https://doi.org/10.1109/WACV.2012.6163026" target="_blank">https://doi.org/10.1109/WACV.2012.6163026</a>
dc.identifier.isbn9781467302333
dc.identifier.issn21583978
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/40501
dc.description.abstractDistinguishing between identical twins is the Holy Grail in face recognition because of the great similarity between the faces of a pair of twins. Most existing face recognition systems choose to simply ignore it. However, as the population of twins increases quickly, such an ostrich strategy is no longer acceptable. The biometric systems that overlook the twins problem are presenting a serious security hole. Inspired by recent advances in motion-based face recognition techniques, we propose to use facial motion to address the twins problem. We collect a twins facial expression database and conduct a series of experiments in two assumed scenarios: the Social Party Scenario and the Access Control Scenario. The experimental results show that facial motion ourperforms facial appearance in distinguishing between twins. Based on this finding, we propose a two-stage cascaded General Access Control System, which combines facial appearance with facial motion. The experimental results show that, compared with an appearance-based face recognition system, this cascaded system is much more secure against an "evil-twin" imposter attack, while performing as good for normal population. © 2012 IEEE.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/WACV.2012.6163026
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.doi10.1109/WACV.2012.6163026
dc.description.sourcetitleProceedings of IEEE Workshop on Applications of Computer Vision
dc.description.page209-214
dc.identifier.isiutNOT_IN_WOS
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