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» Tracking in Reinforcement Learning
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CVPR
2005
IEEE
14 years 4 months ago
Hand Tracking with Flocks of Features
This paper introduces “Flocks of Features,” a fast tracking method for non-rigid and highly articulated objects such as hands. It combines KLT features and a learned foregroun...
Mathias Kölsch, Matthew Turk
AUTOMATICA
2005
116views more  AUTOMATICA 2005»
13 years 10 months ago
Monotonically convergent iterative learning control for linear discrete-time systems
In iterative learning control schemes for linear discrete time systems, conditions to guarantee the monotonic convergence of the tracking9 error norms are derived. By using the Ma...
Kevin L. Moore, Yangquan Chen, Vikas Bahl
CVPR
2009
IEEE
14 years 2 months ago
Learning to associate: HybridBoosted multi-target tracker for crowded scene
We propose a learning-based hierarchical approach of multi-target tracking from a single camera by progressively associating detection responses into longer and longer track fragm...
Yuan Li, Chang Huang, Ram Nevatia
ICONIP
2009
13 years 8 months ago
Robust Incremental Subspace Learning for Object Tracking
In this paper, we introduce a novel incremental subspace based object tracking algorithm. The two major contributions of our work are the Robust PCA based occlusion handling scheme...
Gang Yu, Zhiwei Hu, Hongtao Lu
CVPR
2004
IEEE
15 years 10 days ago
Gibbs Likelihoods for Bayesian Tracking
Bayesian methods for visual tracking model the likelihood of image measurements conditioned on a tracking hypothesis. Image measurements may, for example, correspond to various fi...
Stefan Roth, Leonid Sigal, Michael J. Black