Abstract
We present a technique for face recognition in videos. We are able to recognise a face in a video sequence, given a single gallery image. By assuming that the face is in an approximately frontal position, we jointly model changes in facial appearance caused by identity and illumination. The identity of a face is described by a vector of appearance parameters. We use an angular distance to measure the similarity of faces and a probabilistic procedure to accumulate evidence for recognition along the sequence. We achieve 93.8% recognition success in a set of 65 sequences of 6 subjects from the LaCascia and Sclaroff database. © 2008 Springer-Verlag.
Cite
CITATION STYLE
Buenaposada, J. M., Bekios, J., & Baumela, L. (2008). Apperance-based tracking and face identification in video sequences. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5098 LNCS, pp. 349–358). https://doi.org/10.1007/978-3-540-70517-8_34
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