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» Adaptive object tracking by learning background context
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IVC
2006
183views more  IVC 2006»
14 years 9 months ago
Augmented tracking with incomplete observation and probabilistic reasoning
An on-line algorithm for multi-object tracking is presented for monitoring a real-world scene from a single fixed camera. Potential objects are detected with adaptive backgrounds ...
Ming Xu, Tim Ellis
ICCV
2001
IEEE
15 years 11 months ago
Learning Image Statistics for Bayesian Tracking
This paper describes a framework for learning probabilistic models of objects and scenes and for exploiting these models for tracking complex, deformable, or articulated objects i...
Hedvig Sidenbladh, Michael J. Black
80
Voted
ICCV
2003
IEEE
15 years 11 months ago
On-Line Selection of Discriminative Tracking Features
This paper presents a method for evaluating multiple feature spaces while tracking, and for adjusting the set of features used to improve tracking performance. Our hypothesis is t...
Robert T. Collins, Yanxi Liu
87
Voted
ICIP
2005
IEEE
15 years 11 months ago
Visual tracking via efficient kernel discriminant subspace learning
Robustly tracking moving objects in video sequences is one of the key problems in computer vision. In this paper we introduce a computationally efficient nonlinear kernel learning...
Chunhua Shen, Anton van den Hengel, Michael J. Bro...
ECTEL
2007
Springer
15 years 3 months ago
Community Tools for Repurposing Learning Objects
A critical success factor for the reuse of learning objects is the ease by which they may be repurposed in order to enable reusability in a different teaching context from which th...
Chu Wang, Kate Dickens, Hugh C. Davis, Gary Wills