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ICCV
2009
IEEE
13 years 5 months ago
A robust boosting tracker with minimum error bound in a co-training framework
The varying object appearance and unlabeled data from new frames are always the challenging problem in object tracking. Recently machine learning methods are widely applied to tra...
Rong Liu, Jian Cheng, Hanqing Lu
ML
2010
ACM
119views Machine Learning» more  ML 2010»
13 years 6 months ago
A cooperative coevolutionary algorithm for instance selection for instance-based learning
This paper presents a cooperative evolutionary approach for the problem of instance selection for instance based learning. The presented model takes advantage of one of the most r...
Nicolás García-Pedrajas, Juan Antoni...
CVPR
2005
IEEE
14 years 9 months ago
Tracking Multiple Mouse Contours (without Too Many Samples)
We present a particle filtering algorithm for robustly tracking the contours of multiple deformable objects through severe occlusions. Our algorithm combines a multiple blob track...
Kristin Branson, Serge Belongie
WACV
2005
IEEE
14 years 1 months ago
Learning to Track Objects Through Unobserved Regions
As tracking systems become more effective at reliably tracking multiple objects over extended periods of time within single camera views and across overlapping camera views, incre...
Chris Stauffer
ICCV
2007
IEEE
14 years 1 months ago
Co-Tracking Using Semi-Supervised Support Vector Machines
This paper treats tracking as a foreground/background classification problem and proposes an online semisupervised learning framework. Initialized with a small number of labeled ...
Feng Tang, Shane Brennan, Qi Zhao, Hai Tao