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Proceedings Paper

Pose-robust face recognition using shape-adapted texture features
Author(s): Thorsten Gernoth; André Goossen; Rolf-Rainer Grigat
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Paper Abstract

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.

Paper Details

Date Published: 7 February 2011
PDF: 9 pages
Proc. SPIE 7877, Image Processing: Machine Vision Applications IV, 78770G (7 February 2011); doi: 10.1117/12.872535
Show Author Affiliations
Thorsten Gernoth, Technische Univ. Hamburg-Harburg (Germany)
André Goossen, Technische Univ. Hamburg-Harburg (Germany)
Rolf-Rainer Grigat, Technische Univ. Hamburg-Harburg (Germany)


Published in SPIE Proceedings Vol. 7877:
Image Processing: Machine Vision Applications IV
David Fofi; Philip R. Bingham, Editor(s)

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