We study unsupervised learning of occluding objects in images of visual scenes. The derived learning algorithm is based on a probabilistic generative model which parameterizes obj...
Deformable models in the \physically-based" paradigm are almost always formulated in an ad-hoc fashion, not related to physical reality { they apply the equations on physics i...
Terrance E. Boult, Samuel D. Fenster, Thomas O'Don...
The segmentation of anatomical structures has been traditionally formulated as a perceptual grouping task, and solved through clustering and variational approaches. However, such ...
Bogdan Georgescu, Xiang Sean Zhou, Dorin Comaniciu...
The paper deals with grouping of edges to contours of shapes using only local symmetry and continuity. Shape skeletons are used to generate the search space for a version of the M...
Abstract. In this paper we present a novel tool for body-part segmentation and tracking in the context of multiple camera systems. Our goal is to produce robust motion cues over ti...
Fabio Cuzzolin, Diana Mateus, Edmond Boyer, Radu H...