Automatic Frontal Face Annotation and AAM Building for Arbitrary Expressions from a Single Frontal Image Only
Date
2009
Authors
Asthana, Akshay
Khwaja, Asim
Goecke, Roland
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Institute of Electrical and Electronics Engineers (IEEE Inc)
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.
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Keywords: Active appearance models; Automatic annotation; Error prones; Face images; Facial animation; Facial Expressions; Frontal faces; Manual annotation; Non-rigid objects; Training image; Virtual images; Animation; Computer vision; Imaging systems; Motion Pictu Active Appearance Model (AAM); Automatic annotation; Facial modelling
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Automatic Frontal Face Annotation and AAM Building for Arbitrary Expressions from a Single Frontal Image Only
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Conference paper
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2037-12-31
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