Biometric systems have gained the attention of both the research community and the industry becoming an important topic in real application scenarios. Face recognition is, with fingerprint, among the most used techniques since it is natural for humans to recognize people from facial appearance, since the technology is mature, and because, unlike fingerprint, it is completely unintrusive. Existing systems only focus on the appearance of the subjects considering facial expressions as an obstacle to their aim. On the other hand such systems presents several limitations when dealing with variable illumination conditions, head pose, day-to-day variations (e.g. beard, glasses, or make-up), etc. Furthermore, most of the current techniques do not exploit dynamics to detect the liveness of the tested subjects. In this paper we present a study on person recognition from the dynamics of the facial feature points. The aim of this work is to demonstrate that dynamics of facial expressions could be seen as a biometric characteristic. Therefore, only dynamic characteristics are considered and the adopted features are purged of all appearance information. The results clearly show that relevant biometric information can be extracted from facial expressions and other dynamics of the face.
['Marco Paleari', 'Carmelo Velardo', 'Benoit Huet', 'Jean-Luc Dugelay']
Face dynamics for biometric people recognition