Face recognition under pose variations using shape-adapted texture features

The complexity in face recognition emerges from the variability of the appearance of a human face. While the identity is preserved, the appearance of a face may change due to factors such as illumination, pose or facial expression. To recognize a person independent of pose, we want to separate shape from texture information. We concentrate on the texture part in this work. We first fit an active appearance model to a given facial image. The shape information is used to transform the face into a shape-free 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. The texture features we use for face recognition are independent of pose and shape of the face. We show that these features contain sufficient discriminative information to recognize persons across changes in pose.