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» Tracking People by Learning Their Appearance
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NIPS
2004
13 years 9 months ago
Incremental Learning for Visual Tracking
Most existing tracking algorithms construct a representation of a target object prior to the tracking task starts, and utilize invariant features to handle appearance variation of...
Jongwoo Lim, David A. Ross, Ruei-Sung Lin, Ming-Hs...
CVPR
2010
IEEE
14 years 24 days ago
Visual Tracking via Weakly Supervised Learning from Multiple Imperfect Oracles
Long-term persistent tracking in ever-changing environments is a challenging task, which often requires addressing difficult object appearance update problems. To solve them, most...
Bineng Zhong, Hongxun Yao, Sheng Chen, Xiaotong Yu...
ICASSP
2011
IEEE
12 years 11 months ago
Multiple instance tracking based on hierarchical maximizing bag's margin boosting
In online tracking, the tracker evolves to reflect variations in object appearance and surroundings. This updating process is formulated as a supervised learning problem, thus a ...
Chunxiao Liu, Guijin Wang, Xinggang Lin, Bobo Zeng
ICIP
2010
IEEE
13 years 5 months ago
Face-TLD: Tracking-Learning-Detection applied to faces
A novel system for long-term tracking of a human face in unconstrained videos is built on Tracking-Learning-Detection (TLD) approach. The system extends TLD with the concept of a ...
Zdenek Kalal, Krystian Mikolajczyk, Jiri Matas
CVIU
2006
166views more  CVIU 2006»
13 years 7 months ago
Non-parametric and light-field deformable models
Statistical shape-and-texture appearance models use image morphing to define a rich, compact representation of object appearance. They are useful in a variety of applications incl...
Chris Mario Christoudias, Louis-Philippe Morency, ...