Pose-robust face recognition using shape-adapted texture features

Publikationstyp
Conference Paper
Date Issued
2011-02-07
Sprache
English
Author(s)
Gernoth, Thorsten  
Gooßen, André  
Grigat, Rolf-Rainer  
Institut
Bildverarbeitungssysteme E-2  
TORE-URI
http://hdl.handle.net/11420/10000
First published in
Proceedings of SPIE  
Number in series
7877
Article Number
78770G
Citation
IS&T/SPIE Electronic Imaging (2011)
Contribution to Conference
IS&T/SPIE Electronic Imaging, 2011  
Publisher DOI
10.1117/12.872535
Scopus ID
2-s2.0-79953131797
Publisher
SPIE
ISBN
978-0-8194-8414-7
Unconstrained environments with variable ambient illumination and changes of head pose are still challenging for many face recognition systems. To recognize a person independent of pose, we first fit an active appearance model to a given facial image. Shape information is used to transform the face into a pose-normalized representation. We decompose the transformed face into local regions and extract texture features from these not necessarily rectangular regions using a shape-adapted discrete cosine transform. We show that these features contain sufficient discriminative information to recognize persons across changes in pose. Furthermore, our experimental results show a significant improvement in face recognition performance on faces with pose variations when compared with a block-DCT based feature extraction technique in an access control scenario.
Subjects
active appearance model
discrete cosine transform
face recognition
Infrared imaging
DDC Class
530: Physik
600: Technik
620: Ingenieurwissenschaften
Funding(s)
Kabinentechnologien für komfortable Passagierplattforme  
Funding Organisations
Bundesministerium für Wirtschaft und Technologie
More Funding Information
This work is part of the project KABTEC "Kabinentechnologien für komfortable Passagierplattformen" funded by the German Federal Ministry of Economics and Technology.