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» Novel Observation Model for Probabilistic Object Tracking
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ICCV
2009
IEEE
13 years 6 months ago
Real-time visual tracking via Incremental Covariance Tensor Learning
Visual tracking is a challenging problem, as an object may change its appearance due to pose variations, illumination changes, and occlusions. Many algorithms have been proposed t...
Yi Wu, Jian Cheng, Jinqiao Wang, Hanqing Lu
ICCV
2011
IEEE
12 years 6 months ago
Tracking by Sampling Trackers
We propose a novel tracking framework called visual tracker sampler that tracks a target robustly by searching for the appropriate trackers in each frame. Since the real-world trac...
junseok kwon and kyoung mu lee
CVPR
2008
IEEE
14 years 3 months ago
Global data association for multi-object tracking using network flows
We propose a network flow based optimization method for data association needed for multiple object tracking. The maximum-a-posteriori (MAP) data association problem is mapped in...
Li Zhang, Yuan Li, Ramakant Nevatia
CVPR
2011
IEEE
13 years 23 days ago
Robust Tracking Using Local Sparse Appearance Model and K-Selection
Online learned tracking is widely used for it’s adaptive ability to handle appearance changes. However, it introduces potential drifting problems due to the accumulation of erro...
Baiyang Liu, junzhou Huang, Casimir Kulikowski, Li...
CVPR
2012
IEEE
11 years 11 months ago
Visual tracking via adaptive structural local sparse appearance model
Sparse representation has been applied to visual tracking by finding the best candidate with minimal reconstruction error using target templates. However most sparse representati...
Xu Jia, Huchuan Lu, Ming-Hsuan Yang