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Covariance Features for Trajectory Analysis

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2016

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Institute of Electrical and Electronics Engineers Inc.

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Abstract

In this work, we aimed to demonstrate that covariance estimation methods can be used for trajectory classification. We have shown that, features obtained via shrunk covariance estimation are suitable for describing trajectories. We have arrived to the conclusion that, when compared to Dynamic Time Warping, the explained technique is faster and may yield more accurate results. © 2017 Elsevier B.V., All rights reserved.

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Keywords

Clustering, Dynamic Time Warping, Trajectory Classification

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-- 24th Signal Processing and Communication Application Conference, SIU 2016 -- Zonguldak -- 122605

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1681

End Page

1684
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2

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8

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9

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