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

CORE Recommender
Show full item record

SCOPUSTM   
Citations

81
checked on Mar 21, 2021

WEB OF SCIENCETM
Citations 50

56
Last Week
0
Last month
0
checked on Oct 29, 2023

Page view(s)

507
Last Week
0
Last month
4
checked on Nov 12, 2024

Google ScholarTM

Check

Altmetric


Items in KTISIS are protected by copyright, with all rights reserved, unless otherwise indicated.