7 February 2011 Pose-robust face recognition using shape-adapted texture features
Author Affiliations +
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.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Thorsten Gernoth, André Goossen, 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); doi: 10.1117/12.872535; https://doi.org/10.1117/12.872535

Back to Top