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» An Adaptive Bayesian Technique for Tracking Multiple Objects
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VIP
2003
13 years 9 months ago
Tracking Using CamShift Algorithm and Multiple Quantized Feature Spaces
The Continuously Adaptive Mean Shift Algorithm (CamShift) is an adaptation of the Mean Shift algorithm for object tracking that is intended as a step towards head and face trackin...
John G. Allen, Richard Y. D. Xu, Jesse S. Jin
IJCAI
2003
13 years 9 months ago
Switching Hypothesized Measurements: A Dynamic Model with Applications to Occlusion Adaptive Joint Tracking
This paper proposes a dynamic model supporting multimodal state space probability distributions and presents the application of the model in dealing with visual occlusions when tr...
Yang Wang 0002, Tele Tan, Kia-Fock Loe
JMLR
2012
11 years 10 months ago
Bayesian regularization of non-homogeneous dynamic Bayesian networks by globally coupling interaction parameters
To relax the homogeneity assumption of classical dynamic Bayesian networks (DBNs), various recent studies have combined DBNs with multiple changepoint processes. The underlying as...
Marco Grzegorczyk, Dirk Husmeier
MVA
1998
119views Computer Vision» more  MVA 1998»
13 years 9 months ago
Integrated Techniques for Self-Organisation, Sampling, Habituation, and Motion-Tracking in Visual Robotics Applications
We summarise several techniques in use in our visual robotics research. Our aim is to develop robots that are thoroughly autonomous and adaptable. We describe a system that is ind...
Mark W. Peters, Arcot Sowmya
EVENT
2001
140views more  EVENT 2001»
13 years 9 months ago
Multimodal 3-D Tracking and Event Detection via the Particle Filter
Determining the occurrence of an event is fundamental to developing systems that can observe and react to them. Often, this determination is based on collecting video and/or audio...
Dmitry N. Zotkin, Ramani Duraiswami, Larry S. Davi...