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https://hdl.handle.net/20.500.14279/29291
Τίτλος: | Modelling the variability in face images | Συγγραφείς: | 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 | Λέξεις-κλειδιά: | Shape;Deformable models;Image coding;Biomedical imaging;Biophysics;Optical coupling;Anatomical structure;Image generation;Statistical analysis;Image reconstruction | Ημερομηνία Έκδοσης: | 14-Οκτ-1996 | Πηγή: | 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 | Περίληψη: | 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 |
Εμφανίζεται στις συλλογές: | Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation |
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