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» Multiple Object Tracking with Kernel Particle Filter
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ICASSP
2009
IEEE
13 years 5 months ago
Robust Bayesian tracking on Riemannian manifolds via fragments-based representation
Recently, the covariance region descriptor [1] has been proved robust and versatile for a modest computational cost. It enables efficient fusion of different types of features. Ba...
Yi Wu, Jinqiao Wang, Hanqing Lu
MVA
2007
169views Computer Vision» more  MVA 2007»
13 years 9 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
CVPR
2005
IEEE
14 years 1 months ago
Online Selecting Discriminative Tracking Features Using Particle Filter
The paper proposes a method to keep the tracker robust to background clutters by online selecting discriminative features from a large feature space. Furthermore, the feature sele...
Jianyu Wang, Xilin Chen, Wen Gao
AROBOTS
2010
194views more  AROBOTS 2010»
13 years 6 months ago
Computationally efficient solutions for tracking people with a mobile robot: an experimental evaluation of Bayesian filters
Abstract Modern service robots will soon become an essential part of modern society. As they have to move and act in human environments, it is essential for them to be provided wit...
Nicola Bellotto, Huosheng Hu
ICPR
2006
IEEE
14 years 8 months ago
Real-Time Camera Tracking Using Known 3D Models and a Particle Filter
We present an algorithm which can track the 3D pose of a hand held camera in real-time using predefined models of objects in the scene. The technique utilises and extends recently...
Mark Pupilli, Andrew Calway