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» Probabilistic Object Tracking Using Multiple Features
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ICPR
2004
IEEE
14 years 5 months ago
Probabilistic Object Tracking Using Multiple Features
We present a generic tracker which can handle a variety of different objects. For this purpose, groups of low-level features like interest points, edges, homogeneous and textured ...
David Serby, Esther Koller-Meier, Luc J. Van Gool
PRIS
2001
13 years 6 months ago
Improving the Robustness of Parametric Shape Tracking with Switched Multiple Models
This paper addresses the problem of tracking objects with complex motion dynamics or shape changes. It is assumed that some of the visual features detected in the image (e.g., edg...
Jacinto C. Nascimento, Jorge S. Marques
CVPR
2007
IEEE
14 years 6 months ago
A Bayesian algorithm for tracking multiple moving objects in outdoor surveillance video
Reliable tracking of multiple moving objects in video is an interesting challenge, made difficult in real-world video by various sources of noise and uncertainty. We propose a Bay...
Manjunath Narayana, Donna Haverkamp
CVPR
1999
IEEE
14 years 6 months ago
A Multiple Hypothesis Approach to Figure Tracking
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...
Tat-Jen Cham, James M. Rehg
WSCG
2004
232views more  WSCG 2004»
13 years 6 months ago
Robust Tracking of Athletes Using Multiple Features of Multiple Views
This paper presents a robust and reconfigurable object tracker that integrates multiple visual features from multiple views. The tandem modular architecture stepwise refines the e...
Toshihiko Misu, Seiichi Gohshi, Yoshinori Izumi, Y...