Please use this identifier to cite or link to this item: http://ktisis.cut.ac.cy/handle/10488/245
Title: Automatic interpretation and coding of face images using flexible models
Authors: Taylor, Chris J.
Cootes, Timothy F.
Lanitis, Andreas 
Keywords: Face images
Issue Date: 1997
Publisher: IEEE
Source: Pattern Analysis and Machine Intelligence, IEEE Transactions on, Vol. 19 , no. 7 , 1997, pp. 743 - 756
Abstract: Face images are difficult to interpret because they are highly variable. Sources of variability include individual appearance, 3D pose, facial expression, and lighting. We describe a compact parametrized model of facial appearance which takes into account all these sources of variability. The model represents both shape and gray-level appearance, and is created by performing a statistical analysis over a training set of face images. A robust multiresolution search algorithm is used to fit the model to faces in new images. This allows the main facial features to be located, and a set of shape, and gray-level appearance parameters to be recovered. A good approximation to a given face can be reconstructed using less than 100 of these parameters. This representation can be used for tasks such as image coding, person identification, 3D pose recovery, gender recognition, and expression recognition. Experimental results are presented for a database of 690 face images obtained under widely varying conditions of 3D pose, lighting, and facial expression. The system performs well on all the tasks listed above.
URI: http://ktisis.cut.ac.cy/handle/10488/245
ISSN: 0162-8828
DOI: 10.1109/34.598231
Rights: © Copyright 2009 IEEE – All Rights Reserved.
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