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AVSS
2006
IEEE
13 years 11 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
CVPR
2012
IEEE
11 years 9 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
ICPR
2006
IEEE
14 years 8 months ago
Detection-Assisted Initialization, Adaptation and Fusion of Body Region Trackers for Robust Multiperson Tracking
In this paper, we present a system for simultaneous tracking of multiple persons in a smartroom using multiple cameras. Robust person tracks are created, continuously adapted, and...
Keni Bernardin, Alexander Elbs, Rainer Stiefelhage...
ICCV
2001
IEEE
14 years 9 months ago
BraMBLe: A Bayesian Multiple-Blob Tracker
Blob trackers have become increasingly powerful in recent years largely due to the adoption of statistical appearance models which allow effective background subtraction and robus...
Michael Isard, John MacCormick
MVA
2007
169views Computer Vision» more  MVA 2007»
13 years 8 months ago
Human Tracking Based on Particle Filter in Outdoor Scene
In this paper, we propose the object tracking method based on color histograms and particle filtering. Particle filtering is a time series filter for estimating a state using prob...
Mototsugu Muroi, Heitoh Zen