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