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ICMCS
2007
IEEE
191views Multimedia» more  ICMCS 2007»
14 years 11 days ago
Variable Number of "Informative" Particles for Object Tracking
Particle filter is a sequential Monte Carlo method for object tracking in a recursive Bayesian filtering framework. The efficiency and accuracy of the particle filter depends on t...
Yu Huang, Joan Llach
CVPR
2008
IEEE
14 years 8 months ago
Efficient mean shift belief propagation for vision tracking
A mechanism for efficient mean-shift belief propagation (MSBP) is introduced. The novelty of our work is to use mean-shift to perform nonparametric mode-seeking on belief surfaces...
Minwoo Park, Yanxi Liu, Robert T. Collins
MVA
1994
13 years 7 months ago
Visual Control of a Robot Head
these points must not be coplanar. We report in this article a real time algorithm TIM that can track and estimate hand gesture, providing reliably 5 degrees of freedom from a sing...
Han Wang, Stan Z. Li, Eam Khwang Teoh
ICASSP
2011
IEEE
12 years 9 months ago
Video object tracking with differential Structural SIMilarity index
The Structural SIMilarity Measure (SSIM) combined with the sequential Monte Carlo approach has been shown [1] to achieve more reliable video object tracking performance, compared ...
Artur Loza, Fanglin Wang, Jie Yang, Lyudmila Mihay...
EMMCVPR
2011
Springer
12 years 5 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