For years, researchers in face recognition area have been representing and recognizing faces based on subspace discriminant analysis or statistical learning. Nevertheless, these a...
Conventional subspace learning-based face recognition aims to attain low recognition errors and assumes same loss from all misclassifications. In many real-world face recognition...
Abstract. While face recognition from a single still image has been extensively studied over a decade, face recognition based on more than one still image, such as multiple still i...
One of the major difficulties in face recognition systems is the in-depth pose variation problem. Most face recognition approaches assume that the pose of the face is known. In th...
We present an inherently discriminative approach to face recognition. This is achieved by automatically selecting key points from lines that sketch the face and extracting textural...