This paper analyzes the potential advantages and theoretical challenges of “active learning” algorithms. Active learning involves sequential sampling procedures that use infor...
Abstract. In many vision problems, the observed data lies in a nonlinear manifold in a high-dimensional space. This paper presents a generic modelling scheme to characterize the no...
Ying Zhu, Dorin Comaniciu, Stuart C. Schwartz, Vis...
The main focus of this paper is to present a method of reusing motion captured data by learning a generative model of motion. The model allows synthesis and blending of cyclic moti...
Decision theory does not traditionally include uncertainty over utility functions. We argue that the a person's utility value for a given outcome can be treated as we treat o...
We present a 3D, probabilistic object-surface model, along with mechanisms for probabilistically integrating unregistered 2.5D views into the model, and for segmenting model instan...