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CRV
2009
IEEE
139views Robotics» more  CRV 2009»
14 years 7 months ago
A Multiple Hypothesis Tracking Method with Fragmentation Handling
In this paper, we present a new multiple hypotheses tracking (MHT) approach. Our tracking method is suitable for online applications, because it labels objects at every frame and ...
Atousa Torabi, Guillaume-Alexandre Bilodeau
CVPR
2007
IEEE
15 years 11 months ago
Kernel-based Tracking from a Probabilistic Viewpoint
In this paper, we present a probabilistic formulation of kernel-based tracking methods based upon maximum likelihood estimation. To this end, we view the coordinates for the pixel...
Quang Anh Nguyen, Antonio Robles-Kelly, Chunhua Sh...
ECCV
2000
Springer
15 years 11 months ago
Stochastic Tracking of 3D Human Figures Using 2D Image Motion
A probabilistic method for tracking 3D articulated human figures in monocular image sequences is presented. Within a Bayesian framework, we define a generative model of image appea...
Hedvig Sidenbladh, Michael J. Black, David J. Flee...
ICIP
2007
IEEE
15 years 11 months ago
3D Human Motion Tracking using Manifold Learning
This paper introduces a framework to track 3D human movement using Gaussian process dynamic model (GPDM) and particle filter. The framework combines the particle filter and discri...
Feng Guo, Gang Qian
ICIP
2005
IEEE
15 years 11 months ago
Robust tracking with motion estimation and kernel-based color modelling
Visual tracking is still a challenging problem in computer vision. The applications of Visual Tracking are far-reaching, ranging from surveillance and monitoring to smart rooms. I...
Patrick Bouthemy, Patrick Pérez, R. Venkate...