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» A Probabilistic Framework for Combining Tracking Algorithms
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ICCV
2005
IEEE
14 years 10 months ago
Probabilistic Boosting-Tree: Learning Discriminative Models for Classification, Recognition, and Clustering
In this paper, a new learning framework?probabilistic boosting-tree (PBT), is proposed for learning two-class and multi-class discriminative models. In the learning stage, the pro...
Zhuowen Tu
COMCOM
2006
126views more  COMCOM 2006»
13 years 8 months ago
Distributed and energy-efficient target localization and tracking in wireless sensor networks
In this paper, we propose and evaluate a distributed, energy-efficient, light-weight framework for target localization and tracking in wireless sensor networks. Since radio commun...
Jeongkeun Lee, Kideok Cho, Seungjae Lee, Taekyoung...
WACV
2008
IEEE
14 years 2 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
ICCV
2007
IEEE
14 years 2 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
ICRA
2005
IEEE
146views Robotics» more  ICRA 2005»
14 years 2 months ago
Probabilistic Gaze Imitation and Saliency Learning in a Robotic Head
— Imitation is a powerful mechanism for transferring knowledge from an instructor to a na¨ıve observer, one that is deeply contingent on a state of shared attention between the...
Aaron P. Shon, David B. Grimes, Chris Baker, Matth...