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» Robust Online Appearance Models for Visual Tracking
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ICCV
2007
IEEE
14 years 8 months ago
Robust Visual Tracking Based on Incremental Tensor Subspace Learning
Most existing subspace analysis-based tracking algorithms utilize a flattened vector to represent a target, resulting in a high dimensional data learning problem. Recently, subspa...
Xi Li, Weiming Hu, Zhongfei Zhang, Xiaoqin Zhang, ...
CVPR
2011
IEEE
12 years 10 months 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
2009
IEEE
15 years 1 months ago
Visual Tracking with Online Multiple Instance Learning
In this paper, we address the problem of learning an adaptive appearance model for object tracking. In particular, a class of tracking techniques called “tracking by detection...
Boris Babenko, Ming-Hsuan Yang, Serge J. Belongie
CVPR
2012
IEEE
11 years 8 months ago
Robust visual tracking using autoregressive hidden Markov Model
Recent studies on visual tracking have shown significant improvement in accuracy by handling the appearance variations of the target object. Whereas most studies present schemes ...
Dong Woo Park, Junseok Kwon, Kyoung Mu Lee
FGR
2004
IEEE
230views Biometrics» more  FGR 2004»
13 years 10 months ago
Tracking Humans using Prior and Learned Representations of Shape and Appearance
Tracking a moving person is challenging because a person's appearance in images changes significantly due to articulation, viewpoint changes, and lighting variation across a ...
Jongwoo Lim, David J. Kriegman