Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/29291
Title: Modelling the variability in face images
Authors: Edwards, G.J. 
Lanitis, Andreas 
Taylor, Chris J. 
Cootes, Timothy F. 
Major Field of Science: Natural Sciences;Engineering and Technology
Field Category: Computer and Information Sciences;Biological Sciences;Design
Keywords: Shape;Deformable models;Image coding;Biomedical imaging;Biophysics;Optical coupling;Anatomical structure;Image generation;Statistical analysis;Image reconstruction
Issue Date: 14-Oct-1996
Source: Proceedings of the Second International Conference on Automatic Face and Gesture Recognition, 1996, Killington, USA, p.p.328-333
Start page: 328
End page: 333
Conference: Second International Conference on Automatic Face and Gesture Recognition 
Abstract: Model based approaches to the interpretation of face images have proved very successful. We have previously described statistically based models of face shape and grey-level appearance and shown how they can be used to perform various coding and interpretation tasks. In the paper we describe improved methods of modelling which couple shape and grey-level information more directly than our existing methods, isolate the changes in appearance due to different sources of variability (person, expression, pose, lighting), and deal with nonlinear shape variation. We show that the new methods are better suited to interpretation and tracking tasks.
URI: https://hdl.handle.net/20.500.14279/29291
DOI: 10.1109/AFGR.1996.557286
Type: Conference Papers
Affiliation : The University of Manchester 
Appears in Collections:Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation

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