Person recognition using facial video information : A state of the art

Matta, Federico; Dugelay, Jean-Luc
Journal of Visual Languages, Volume 20, Issue 3, June 2009

In this article we propose a detailed state of the art on person recognition using facial video information. We classify the existing approaches present in the scientific literature between those that neglect the temporal information, and those that exploit it even partially. Concerning the first category, we detail the extensions to video data of: eigenfaces, fisherfaces, active appearance models (AAMs), radial basis function neural networks (RBFNNs), elastic graph matching (EGM), hierarchical discriminative regression trees (HDRTs) and pairwise clustering methods. After that, we focus on the strategies exploiting the temporal information, in particular those analysing: the facial motion with optical flow, the evolution of facial appearance over time with hidden Markov models (HMMs) or with various probabilistic tracking and recognition approaches, and the head motion with Gaussian mixture models.


DOI
Type:
Journal
Date:
2009-06-30
Department:
Digital Security
Eurecom Ref:
3198
Copyright:
© Elsevier. Personal use of this material is permitted. The definitive version of this paper was published in Journal of Visual Languages, Volume 20, Issue 3, June 2009 and is available at : http://dx.doi.org/10.1016/j.jvlc.2009.01.002

PERMALINK : https://www.eurecom.fr/publication/3198