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» Tracking the Invisible: Learning Where the Object Might be
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CVPR
2009
IEEE
15 years 26 days ago
Discriminatively Trained Particle Filters for Complex Multi-Object Tracking
This work presents a discriminative training method for particle filters in the context of multi-object tracking. We are motivated by the difficulty of hand-tuning the many mode...
Alan Fern, Robin Hess
ICIP
2005
IEEE
14 years 7 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...
ICPR
2006
IEEE
14 years 6 months ago
Audio-Visual Speaker Localization Using Graphical Models
In this work we propose an approach to combine audio and video modalities for person tracking using graphical models. We demonstrate a principled and intuitive framework for combi...
Akash Kushal, Mandar Rahurkar, Fei-Fei Li 0002, Je...
CVPR
2012
IEEE
11 years 8 months ago
Robust visual tracking using autoregressive hidden Markov Model
Recent studies on visual tracking have shown significant improvement in accuracy by handling the appearance variations of the target object. Whereas most studies present schemes ...
Dong Woo Park, Junseok Kwon, Kyoung Mu Lee
AVSS
2006
IEEE
13 years 9 months ago
Classification-Based Likelihood Functions for Bayesian Tracking
The success of any Bayesian particle filtering based tracker relies heavily on the ability of the likelihood function to discriminate between the state that fits the image well an...
Chunhua Shen, Hongdong Li, Michael J. Brooks