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Pattern Analysis and Applications
Erschienen in: Pattern Analysis and Applications 1/2008

01.01.2008 | Theoretical Advances

Recognising facial expressions in video sequences

verfasst von: José M. Buenaposada, Enrique Muñoz, Luis Baumela

Erschienen in: Pattern Analysis and Applications | Ausgabe 1/2008

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Abstract

We introduce a system that processes a sequence of images of a front-facing human face and recognises a set of facial expressions. We use an efficient appearance-based face tracker to locate the face in the image sequence and estimate the deformation of its non-rigid components. The tracker works in real time. It is robust to strong illumination changes and factors out changes in appearance caused by illumination from changes due to face deformation. We adopt a model-based approach for facial expression recognition. In our model, an image of a face is represented by a point in a deformation space. The variability of the classes of images associated with facial expressions is represented by a set of samples which model a low-dimensional manifold in the space of deformations. We introduce a probabilistic procedure based on a nearest-neighbour approach to combine the information provided by the incoming image sequence with the prior information stored in the expression manifold to compute a posterior probability associated with a facial expression. In the experiments conducted we show that this system is able to work in an unconstrained environment with strong changes in illumination and face location. It achieves an 89% recognition rate in a set of 333 sequences from the Cohn–Kanade database.
Vorheriger Artikel Diagnosis of lung nodule using Moran’s index and Geary’s coefficient in computerized tomography images

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Metadaten
Titel
Recognising facial expressions in video sequences
verfasst von
José M. Buenaposada
Enrique Muñoz
Luis Baumela
Publikationsdatum
01.01.2008
Verlag
Springer-Verlag
Erschienen in
Pattern Analysis and Applications / Ausgabe 1/2008
Print ISSN: 1433-7541
Elektronische ISSN: 1433-755X
DOI
https://doi.org/10.1007/s10044-007-0084-8

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