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ICMCS
2007
IEEE
191views Multimedia» more  ICMCS 2007»
14 years 1 months 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 9 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 8 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 11 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 7 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