Pose-robust face recognition using shape-adapted texture features

Thorsten Gernoth; André Goossen; Rolf-Rainer Grigat

doi:10.1117/12.872535

7 February 2011 Pose-robust face recognition using shape-adapted texture features

Thorsten Gernoth, André Goossen, Rolf-Rainer Grigat

Proceedings Volume 7877, Image Processing: Machine Vision Applications IV; 78770G (2011) https://doi.org/10.1117/12.872535
Event: IS&T/SPIE Electronic Imaging, 2011, San Francisco Airport, California, United States

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.

Citation Download Citation

Thorsten Gernoth, André Goossen, and Rolf-Rainer Grigat "Pose-robust face recognition using shape-adapted texture features", Proc. SPIE 7877, Image Processing: Machine Vision Applications IV, 78770G (7 February 2011); https://doi.org/10.1117/12.872535

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KEYWORDS

Facial recognition systems

Feature selection

Head

Databases

Feature extraction

Cameras

Statistical modeling

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