Pattern Analysis and Applications

, Volume 11, Issue 1, pp 101–116

Recognising facial expressions in video sequences

  • José M. Buenaposada
  • Enrique Muñoz
  • Luis Baumela
Theoretical Advances

DOI: 10.1007/s10044-007-0084-8

Cite this article as:
Buenaposada, J.M., Muñoz, E. & Baumela, L. Pattern Anal Applic (2008) 11: 101. doi:10.1007/s10044-007-0084-8


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.


Facial expression recognitionManifold of facial expressionsNearest neighbour

Copyright information

© Springer-Verlag London Limited 2007

Authors and Affiliations

  • José M. Buenaposada
    • 1
  • Enrique Muñoz
    • 2
    • 3
  • Luis Baumela
    • 2
  1. 1.ESCETUniversidad Rey Juan CarlosMóstolesSpain
  2. 2.Facultad InformáticaUniversidad Politécnica de MadridBoadilla del MonteSpain
  3. 3.Facultad InformáticaUniversidad Complutense de MadridMadridSpain