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Proceedings Paper

Fusing shape and texture features for pose-robust face recognition
Author(s): Thorsten Gernoth; 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 separate shape from texture information using an active appearance model. We do not directly use the texture information from the active appearance model for recognition. Instead we extract local texture features from a shape and pose free representation of facial images. We use a smooth warp function to transform the images. We compensate also the shape information for head pose changes and fuse the results of separate classiers for shape features and local texture features. We analyze the inuence of the individual contributions of shape and texture information on the recognition performance. We show that fusing shape and texture information can boost the recognition performance in an access control scenario.

Paper Details

Date Published: 2 February 2012
PDF: 10 pages
Proc. SPIE 8300, Image Processing: Machine Vision Applications V, 830006 (2 February 2012); doi: 10.1117/12.909070
Show Author Affiliations
Thorsten Gernoth, Technische Univ. Hamburg-Harburg (Germany)
Rolf-Rainer Grigat, Technische Univ. Hamburg-Harburg (Germany)


Published in SPIE Proceedings Vol. 8300:
Image Processing: Machine Vision Applications V
Philip R. Bingham; Edmund Y. Lam, Editor(s)

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