This paper aims to develop a new statistical measure to identify significant correlations among multiple events with spatial and temporal components. This new measure, ( , )K r t ,...
In many vision problems, instead of having fully labeled training data, it is easier to obtain the input in small groups, where the data in each group is constrained to be from th...
In 3D face recognition systems, 3D facial shape information plays an important role. 3D face recognizers usually depend on point cloud representation of faces where faces are repre...
Principle Component Analysis (PCA) technique is an important and well-developed area of image recognition and to date many linear discrimination methods have been put forward. Desp...
In this paper, we develop a geometric framework for linear or nonlinear discriminant subspace learning and classification. In our framework, the structures of classes are conceptu...