A new method for tracking contours of moving objects in clutter is presented. For a given object, a model of its contours is learned from training data in the form of a subset of c...
In this paper, we propose a novel manifold alignment method by learning the underlying common manifold with supervision of corresponding data pairs from different observation sets...
Deming Zhai, Bo Li, Hong Chang, Shiguang Shan, Xil...
We introduce a robust probabilistic approach to modeling shape contours based on a lowdimensional, nonlinear latent variable model. In contrast to existing techniques that use obj...
Abstract: Although immense efforts have been invested in the construction of hundreds of learning object repositories, the degree of reuse of learning resources maintained in such ...
In a large sensor network, in-network data aggregation, i.e., combining partial results at intermediate nodes during message routing, significantly reduces the amount of communic...