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» Robust Incremental Subspace Learning for Object Tracking
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IWCM
2004
Springer
14 years 25 days ago
Tracking Complex Objects Using Graphical Object Models
We present a probabilistic framework for component-based automatic detection and tracking of objects in video. We represent objects as spatio-temporal two-layer graphical models, w...
Leonid Sigal, Ying Zhu, Dorin Comaniciu, Michael J...
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
CVPR
2010
IEEE
13 years 12 months ago
An Online Approach: Learning-Semantic-Scene-by-Tracking and Tracking-by-Learning-Semantic-Scene
Learning the knowledge of scene structure and tracking a large number of targets are both active topics of computer vision in recent years, which plays a crucial role in surveilla...
Xuan Song, Xiaowei Shao, Huijing Zhao, Jinshi Cui,...
ECCV
2004
Springer
14 years 9 months ago
Tracking Aspects of the Foreground against the Background
In object tracking, change of object aspect is a cause of failure due to significant changes of object appearances. The paper proposes an approach to this problem without a priori ...
Hieu Tat Nguyen, Arnold W. M. Smeulders
ISMAR
2009
IEEE
14 years 2 months ago
Augmenting text document by on-line learning of local arrangement of keypoints
We propose a technique for text document tracking over a large range of viewpoints. Since the popular SIFT or SURF descriptors typically fail on such documents, our method conside...
Hideaki Uchiyama, Hideo Saito