Gernoth, ThorstenThorstenGernothGooßen, AndréAndréGooßenGrigat, Rolf-RainerRolf-RainerGrigat2021-07-292021-07-292011-02-07IS&T/SPIE Electronic Imaging (2011)978-0-8194-8414-7http://hdl.handle.net/11420/10000Unconstrained 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. © 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).enactive appearance modeldiscrete cosine transformface recognitionInfrared imagingPhysikTechnikIngenieurwissenschaftenConference Paper10.1117/12.872535Conference Paper