Infrared Object Tracking Algorithm Based on Online AdaBoost

Abstract:

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An online AdaBoost based tracking algorithm in FLIR imagery is proposed, where tracking is formulated as a binary classification problem. The object features are selected adaptively via online boosting. And then, a strong classifier is built on the weak classifiers. The confidence map of consecutive image frame is created by the strong classifier. The object localization is realized by detecting maximum of the confidence map using mean shift. The weak classfiers are updated according to the new samples to improve the discriminative ability to the object appearance and complex scene. Experiment results verify the effectives and robustness of this tracking algorithm which can improve the tracking performance efficiently.

Info:

Periodical:

Advanced Materials Research (Volumes 443-444)

Edited by:

Li Jian

Pages:

447-451

DOI:

10.4028/www.scientific.net/AMR.443-444.447

Citation:

J. S. Li et al., "Infrared Object Tracking Algorithm Based on Online AdaBoost", Advanced Materials Research, Vols. 443-444, pp. 447-451, 2012

Online since:

January 2012

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Price:

$35.00

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