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» An appearance based approach for human and object tracking
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CVPR
2012
IEEE
13 years 8 days ago
Multi-target tracking by online learning of non-linear motion patterns and robust appearance models
We describe an online approach to learn non-linear motion patterns and robust appearance models for multi-target tracking in a tracklet association framework. Unlike most previous...
Bo Yang, Ram Nevatia
ICPR
2006
IEEE
15 years 11 months ago
Robust Image Registration Based on Markov-Gibbs Appearance Model
A new approach to align an image of a textured object with a given prototype is proposed. Visual appearance of the images, after equalizing their signals, is modeled with a Markov...
Alaa E. Abdel-Hakim, Aly A. Farag, Ayman El-Baz, G...
CVPR
2004
IEEE
15 years 12 months ago
An Algorithm for Multiple Object Trajectory Tracking
Most tracking algorithms are based on the maximum a posteriori (MAP) solution of a probabilistic framework called Hidden Markov Model, where the distribution of the object state a...
Mei Han, Wei Xu, Hai Tao, Yihong Gong
CVPR
2003
IEEE
15 years 12 months ago
Probabilistic Tracking in Joint Feature-Spatial Spaces
In this paper we present a probabilistic framework for tracking regions based on their appearance. We exploit the feature-spatial distribution of a region representing an object a...
Ahmed M. Elgammal, Ramani Duraiswami, Larry S. Dav...
CVPR
2010
IEEE
15 years 6 months ago
Visual Object Tracking using Adaptive Correlation Filters
Although not commonly used, correlation filters can track complex objects through rotations, occlusions and other distractions at over 20 times the rate of current state-ofthe-ar...
David Bolme, J Ross Beveridge, Bruce Draper, Yui M...