This paper presents the evaluation results of a system for tracking humans in surveillance videos. Moving blobs are detected based on adaptive background modeling. A shape based mu...
Bo Wu, Vivek Kumar Singh, C.-H. Kuo, Li Zhang, Sun...
We present a Bayesian framework for learning higherorder transition models in video surveillance networks. Such higher-order models describe object movement between cameras in the...
This paper presents a novel approach to detect and track pedestrians and cars based on the combined information retrieved from a camera and a laser range scanner. Laser data points...
Luciano Spinello, Rudolph Triebel, Roland Siegwart
In many tracking scenarios, the amplitude of target returns are stronger than those coming from false alarms. This information can be used to improve the multi-target state estimat...
Daniel Clark, Branko Ristic, Ba-Ngu Vo, Ba-Tuong V...
This paper considers the problem of Bayesian inference in dynamical models with time-varying dimension. These models have been studied in the context of multiple target tracking pr...