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» 3D Tracking by Catadioptric Vision Based on Particle Filters
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ICPR
2006
IEEE
14 years 7 months ago
An integrated Monte Carlo data association framework for multi-object tracking
We propose a sequential Monte Carlo data association algorithm based on a two-level computational framework for tracking varying number of interacting objects in dynamic scene. Fi...
Jianru Xue, Nanning Zheng, Xiaopin Zhong
EMMCVPR
2011
Springer
12 years 6 months ago
Data-Driven Importance Distributions for Articulated Tracking
Abstract. We present two data-driven importance distributions for particle filterbased articulated tracking; one based on background subtraction, another on depth information. In ...
Søren Hauberg, Kim Steenstrup Pedersen
CVPR
2007
IEEE
14 years 8 months ago
In Situ Evaluation of Tracking Algorithms Using Time Reversed Chains
Automatic evaluation of visual tracking algorithms in the absence of ground truth is a very challenging and important problem. In the context of online appearance modeling, there ...
Hao Wu, Aswin C. Sankaranarayanan, Rama Chellappa
ICCV
2007
IEEE
14 years 8 months ago
Probabilistic Color and Adaptive Multi-Feature Tracking with Dynamically Switched Priority Between Cues
We present a probabilistic multi-cue tracking approach constructed by employing a novel randomized template tracker and a constant color model based particle filter. Our approach ...
François Le Clerc, Lionel Oisel, Patrick P&...
CVPR
2004
IEEE
14 years 8 months ago
Multi-Scale Visual Tracking by Sequential Belief Propagation
A novel statistical method is proposed in this paper to overcome abrupt motion for robust visual tracking. Existing tracking methods that are based on the small motion assumption ...
Gang Hua, Ying Wu