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...
Object tracking with multiple cameras is more efficient than tracking with one camera. In this paper, we propose a multiple-camera multiple-object tracking system that can track 3D...
This paper presents a computer vision system for tracking and predicting flying balls in 3-D from a stereo-camera. It pursues a “textbook-style” approach with a robust circle ...
— Mobile robots operating in populated environments typically can improve their service and navigation behavior when they know where people are in their vicinity and in which dir...
— Classic registration methods for model-based tracking try to align the projected edges of a 3D model with the edges of the image. However, wrong matches at low level can make t...