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CIRA
2007
IEEE
179views Robotics» more  CIRA 2007»
14 years 2 months ago
Learning Tactic-Based Motion Models of a Moving Object with Particle Filtering
— Learning motion models of a moving object is a challenge for autonomous robots. We address the particular instance of parameter learning when tracking object motions in a switc...
Yang Gu, Manuela M. Veloso
VMV
2008
116views Visualization» more  VMV 2008»
13 years 9 months ago
A GPU-accelerated particle filter with pixel-level likelihood
We present in this paper a GPU-accelerated particle filter based on pixel-level segmentation and matching, for real-time object tracking. The proposed method achieves real-time pe...
Claus Lenz, Giorgio Panin, Alois Knoll
IJCV
2008
188views more  IJCV 2008»
13 years 8 months ago
Partial Linear Gaussian Models for Tracking in Image Sequences Using Sequential Monte Carlo Methods
The recent development of Sequential Monte Carlo methods (also called particle filters) has enabled the definition of efficient algorithms for tracking applications in image sequen...
Elise Arnaud, Étienne Mémin
ICCV
2003
IEEE
14 years 9 months ago
Tracking Articulated Body by Dynamic Markov Network
A new method for visual tracking of articulated objects is presented. Analyzing articulated motion is challenging because the dimensionality increase potentially demands tremendou...
Ying Wu, Gang Hua, Ting Yu
ICIP
2005
IEEE
14 years 9 months ago
Bayesian visual tracking with existence process
Most object tracking approaches either assume that the number of objects is constant, or that information about object existence is provided by some external source. Here, we show...
Jaco Vermaak, Mark Briers, Patrick Pérez, S...