Most face recognition algorithms use a “distancebased” approach: gallery and probe images are projected into a low dimensional feature space and decisions about matching are b...
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--Rough face alignments lead to suboptimal performance of face identification systems. In this study, we present a novel approach for identifying genders from facial images...
The variations of pose lead to significant performance
decline in face recognition systems, which is a bottleneck
in face recognition. A key problem is how to measure the
simila...
Annan Li (Chinese Academy of Sciences), Shiguang S...
A major challenge for face recognition algorithms lies in the variance faces undergo while changing pose. This problem is typically addressed by building view dependent models bas...