We derive a probabilistic framework for robust, realtime, visual tracking of multiple previously unseen objects from a moving camera. This framework models the discrete depth orde...
Visual tracking is a challenging problem, as an object may change its appearance due to viewpoint variations, illumination changes, and occlusion. Also, an object may leave the fie...
— In this paper we present a novel approach to robust visual servoing. This method removes the feature tracking step from a typical visual servoing algorithm. We do not need corr...
Abstract. This paper describes a framework for analyzing video sequences of a driver and determining his level of attention. The proposed system deals with the computation of eyeli...
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...