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» Adaptive object tracking by learning background context
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WACV
2008
IEEE
15 years 4 months ago
Likelihood Map Fusion for Visual Object Tracking
Visual object tracking can be considered as a figure-ground classification task. In this paper, different features are used to generate a set of likelihood maps for each pixel i...
Zhaozheng Yin, Fatih Porikli, Robert T. Collins
ICIP
1999
IEEE
15 years 11 months ago
Adaptive Wavelet-Packet Decomposition for Rate Control of Object Oriented Coding of Video Sequences
A novel object dependent coding scheme based on optimization upon wavelet packet trees is proposed. The method may be employed in the context of object oriented video standard MPE...
Ioannis Stephanakis, Anastasios D. Doulamis, Nikol...
NIPS
2004
14 years 11 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...
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CVPR
2010
IEEE
15 years 2 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,...
ICCV
2007
IEEE
15 years 4 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