This paper presents a novel approach to particle filtering which minimizes the total tracking distortion by considering dynamic variance of proposal density and adaptive number o...
The likelihood models used in probabilistic visual tracking applications are often complex non-linear and/or nonGaussian functions, leading to analytically intractable inference. ...
Visual tracking is one of the key tasks in computer vision. The particle filter algorithm has been extensively used to tackle this problem due to its flexibility. However the conv...
Chunhua Shen, Michael J. Brooks, Anton van den Hen...
Robust visual tracking has become an important topic in the field of computer vision. The integration of cues such as color, edge strength and motion has proved to be a promising ...
Chunhua Shen, Anton van den Hengel, Anthony R. Dic...
Abstract. This paper presents a novel probabilistic approach to integrating multiple cues in visual tracking. We perform tracking in different cues by interacting processes. Each p...