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» Real-Time Tracking of Non-Rigid Objects Using Mean Shift
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CVPR
2007
IEEE
14 years 9 months ago
Optimizing Distribution-based Matching by Random Subsampling
We boost the efficiency and robustness of distributionbased matching by random subsampling which results in the minimum number of samples required to achieve a specified probabili...
Alex Po Leung, Shaogang Gong
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
ICCV
2007
IEEE
14 years 9 months ago
Differential EMD Tracking
Illumination changes cause object appearance to change drastically and many existing tracking algorithms lack the capability to handle this problem. The Earth Mover's Distanc...
Qi Zhao, Shane Brennan, Hai Tao
ICCCN
2007
IEEE
13 years 7 months ago
Online Selection of Tracking Features using AdaBoost
In this paper, a novel feature selection algorithm for object tracking is proposed. This algorithm performs more robust than the previous works by taking the correlation between f...
Ying-Jia Yeh, Chiou-Ting Hsu
CVPR
2010
IEEE
14 years 29 days ago
Novel Observation Model for Probabilistic Object Tracking
Treating visual object tracking as foreground and background classification problem has attracted much attention in the past decade. Most methods adopt mean shift or brute force s...
Dawei Liang, Qingming Huang, Hongxun Yao, Shuqiang...