Autori: Irene Kotsia, Ioan Buciu and Ioannis Pitas

Editorial: Journal of Image and Visual Computing, 26 (7), p.1052-1067, 2008.

Rezumat:

In this paper, an analysis of the effect of partial occlusion on facial expression recognition is investigated. The classification from partially occluded images in one of the six basic facial expressions is performed using a method based on Gabor-wavelets texture information extraction, a supervised image decomposition method based on Discriminant Non-negative Matrix Factorization and a shape based method that exploits the geometrical displacement of certain facial features. We demonstrate how partial occlusion affects the above mentioned methods in
the classification of the six basic facial expressions, and indicate the way
partial occlusion affects human observers when recognizing facial expressions. An attempt to specify which part of the face (eyes, mouth, lower or upper region) contains more discriminant information for each facial expression, is also made and conclusions regarding the pairs of facial expressions misclassifications that each type of occlusion introduces, are drawn.

Cuvinte cheie: Facial expression recognition, Gabor filters, Discriminant Nonnegative Matrix Factorization, Support Vector Machines, partial occlusion.

URL: http://portal.acm.org/citation.cfm?id=1365094.1365275&coll=GUIDE&dl=GUIDE