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218
Voted
CVPR
2009
IEEE
2305views Computer Vision» more  CVPR 2009»
16 years 9 months ago
Visual tracking on the affine group via geometric particle filtering using optimal importance function
We propose a geometric method for visual tracking, in which the 2-D affine motion of a given object template is estimated in a video sequence by means of coordinateinvariant partic...
Junghyun Kwon (Seoul National University), Kyoung ...
127
Voted
CVPR
1999
IEEE
16 years 3 months ago
A Multiple Hypothesis Approach to Figure Tracking
This paper describes a probabilistic multiple-hypothesis framework for tracking highly articulated objects. In this framework, the probability density of the tracker state is repr...
Tat-Jen Cham, James M. Rehg
CVPR
2005
IEEE
16 years 3 months ago
Visual Tracking in the Presence of Motion Blur
We consider the problem of visual tracking of regions of interest in a sequence of motion blurred images. Traditional methods couple tracking with deblurring in order to correctly...
Hailin Jin, Paolo Favaro, Roberto Cipolla
CVPR
2005
IEEE
16 years 3 months ago
Using Particles to Track Varying Numbers of Interacting People
In this paper, we present a Bayesian framework for the fully automatic tracking of a variable number of interacting targets using a fixed camera. This framework uses a joint multi...
Kevin Smith, Daniel Gatica-Perez, Jean-Marc Odobez
114
Voted
ICPR
2006
IEEE
16 years 2 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