Automatic frontal face annotation and AAM building for arbitrary expressions from a single frontal image only

Authors:
Akshay Asthana;Asim Khwaja;Roland Goecke
Affiliations:
RSISE, CECS, Australian National University, Canberra, Australia;RSISE, CECS, Australian National University, Canberra, Australia;RSISE, CECS, Australian National University, Canberra, Australia and HCC Lab, NCBS, Faculty of Information Sciences and Engineering, University of Canberra, Australia
Venue:
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Year:
2009

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Abstract

In recent years, statistically motivated approaches for the registration and tracking of non-rigid objects, such as the Active Appearance Model (AAM), have become very popular. A major drawback of these approaches is that they require manual annotation of all training images which can be tedious and error prone. In this paper, a MPEG-4 based approach for the automatic annotation of frontal face images, having any arbitrary facial expression, from a single annotated frontal image is presented. This approach utilises the MPEG-4 based facial animation system to generate virtual images having different expressions and uses the existing AAM framework to automatically annotate unseen images. The approach demonstrates an excellent generalisability by automatically annotating face images from two different databases.