Bayesian analysis is a popular subspace based face recognition method. It casts the face recognition task into a binary classification problem with each of the two classes, intrap...
Central and subspace clustering methods are at the core of many segmentation problems in computer vision. However, both methods fail to give the correct segmentation in many pract...
In this paper, we present a probabilistic algorithm for visual tracking that incorporates robust template matching and incremental subspace update. There are two template matching...
Nearest neighbour classifiers and related kernel methods often perform poorly in high dimensional problems because it is infeasible to include enough training samples to cover the...
Linear Discriminant Analysis (LDA) is a widely used technique for pattern classification. It seeks the linear projection of the data to a low dimensional subspace where the data ...