New hope for recognizing twins by using facial motion

Distinguishing 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.