In Proc. of IEEE Conf. on CVPR'03, Madison, Wisconsin, 2003 We propose a generative model approach to contour tracking against non-stationary clutter and to coping with occlu...
In this paper we present a method for learning a curve model for detection and segmentation by closely integrating a hierarchical curve representation using generative and discrim...
Adrian Barbu, Vassilis Athitsos, Bogdan Georgescu,...
A central challenge in systems biology is the reconstruction of biological networks from high-throughput data sets. A particularly difficult case of this is the inference of dynami...
Michael Baym, Chris Bakal, Norbert Perrimon, Bonni...
This paper proposes an appearance generative mixture model based on key frames for meanshift tracking. Meanshift tracking algorithm tracks object by maximizing the similarity betwe...
We present a probabilistic framework for component-based automatic detection and tracking of objects in video. We represent objects as spatio-temporal two-layer graphical models, w...
Leonid Sigal, Ying Zhu, Dorin Comaniciu, Michael J...