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2008
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Tracking interacting targets with laser scanner via on-line supervised learning

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Tracking interacting targets with laser scanner via on-line supervised learning
— Successful multi-target tracking requires locating the targets and labeling their identities. For the laser based tracking system, the latter becomes significantly more challenging when the targets frequently interact with each other. This paper presents a novel on-line supervised learning based method for tracking interacting targets with laser scanner. When the targets do not interact with each other, we collect samples and train a classifier for each target. When the targets are in close proximity, we use these classifiers to assist in tracking. Different evaluations demonstrate that this method has a better tracking performance than previous methods when interactions occur, and can maintain correct tracking under various complex tracking situations.
Xuan Song, Jinshi Cui, Xulei Wang, Huijing Zhao, H
Added 30 May 2010
Updated 30 May 2010
Type Conference
Year 2008
Where ICRA
Authors Xuan Song, Jinshi Cui, Xulei Wang, Huijing Zhao, Hongbin Zha
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