Visual Tracking Based on an Improved Online Multiple Instance Learning Algorithm

An improved online multiple instance learning (IMIL) for a visual tracking algorithm is proposed. In the IMIL algorithm, the importance of each instance contributing to a bag probability is with respect to their probabilities. A selection strategy based on an inner product is presented to choose wea...

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Veröffentlicht in:	Computational Intelligence and Neuroscience Jg. 2016; H. 2016; S. 637 - 645-054
Hauptverfasser:	Wang, Li Jia, Zhang, Hua
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Cairo, Egypt Hindawi Limiteds 01.01.2016 Hindawi Publishing Corporation John Wiley & Sons, Inc
Schlagworte:	Algorithms Ambiguity Artificial Intelligence Attention - physiology Classifiers Distance learning Eye Movements - physiology Feedback Histograms Humans Learning Learning - physiology Machine learning Mathematical research Methods Online Systems Photic Stimulation Probability Strategy Technology application Tracking Visual China
ISSN:	1687-5265, 1687-5273
Online-Zugang:	Volltext
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