Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/1931
Title: | Statistical models of face images--improving specificity | Authors: | Edwards, Gareth J. Taylor, Chris J. Cootes, Timothy F. Lanitis, Andreas |
metadata.dc.contributor.other: | Λανίτης, Ανδρέας | Major Field of Science: | Engineering and Technology | Keywords: | Face image interpretation;Model-based approach | Issue Date: | Mar-1998 | Source: | Image and Vision Computing, 1998, vol. 16, no. 3, pp. 203-211 | Volume: | 16 | Issue: | 3 | Start page: | 203 | End page: | 211 | Journal: | Image and Vision Computing | 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 non-linear shape variation. We show that the new methods are better suited to interpretation and tracking tasks. | URI: | https://hdl.handle.net/20.500.14279/1931 | ISSN: | 2628856 | DOI: | 10.1016/S0262-8856(97)00069-3 | Rights: | © Elsevier | Type: | Article | Affiliation : | The University of Manchester |
Appears in Collections: | Άρθρα/Articles |
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