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Online Visual Multiple Target Tracking by Intuitionistic Fuzzy Data Association
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Journal Article
Online Visual Multiple Target Tracking by Intuitionistic Fuzzy Data Association
2017
Overview
In this paper, a novel frame-by-frame data association algorithm based on intuitionistic fuzzy sets is proposed for online visual multiple target tracking. In the proposed algorithm, the association costs between targets and measurements are replaced by the intuitionistic fuzzy membership degrees which are obtained by a modified intuitionistic fuzzy c-means clustering algorithm. In addition, in order to mine useful information from the uncertain measurements, a new intuitionistic index is defined and the intuitionistic fuzzy point operator is applied to extract valuable information from the intuitionistic index. Experiments with challenging public datasets demonstrate that the proposed visual tracking algorithm improves tracking performance compared to other algorithms.
Publisher
Springer Berlin Heidelberg,Springer Nature B.V
