Output details
11 - Computer Science and Informatics
University of Portsmouth
Article title
Facial Expression Biometrics Using Statistical Shape Models
Type
D - Journal article
Title of journal
EURASIP Journal on Advances in Signal Processing
Article number
-
Volume number
2009
Issue number
-
First page of article
1
ISSN of journal
1687-6180
Year of publication
2009
URL
-
Number of additional authors
3
Additional information
<23>Common face recognition algorithms suffer from undesirable consequences related to illumination, background clutter and viewing angles. This paper reports a novel technique for facial expression recognition that overcomes most of these limitations. It is based on the statistical shape model (SSM) that relies primarily on shape information thus disregarding texture information inherent in face images. This work enabled further extensions to develop a Hi-Resolution 3D dynamic facial articulation database and research into the diagnostics of facial dysfunctions of neurological patients supported by EPSRC grant EP/H024913/1.
Interdisciplinary
-
Cross-referral requested
-
Research group
None
Citation count
2
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-
