This paper describes a probabilistic multiple-hypothesis framework for tracking highly articulated objects. In this framework, the probability density of the tracker state is repr...
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...
This paper presents an approach to image filtering that is driven by the properties of the iso-valued level curves of the image and their relationship with one another. We explore...
In this paper, we bring out a new density-based clustering initialization algorithm which is invariant to the scale factor. Instead of using the scale factor while the cluster ini...
We describe our experience with a new algorithm for the reconstruction of surfaces from unorganized sample points in IR 3. The algorithm is the first for this problem with provab...
Nina Amenta, Marshall W. Bern, Manolis Kamvysselis