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Covariance Features for Trajectory Analysis

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Date

2016

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Journal ISSN

Volume Title

Publisher

IEEE

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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.

Description

Maras, Hadi Hakan/0000-0001-5117-3938

Keywords

Trajectory Classification, Dynamic Time Warping, Clustering

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Citation

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Source

24th Signal Processing and Communication Application Conference (SIU) -- MAY 16-19, 2016 -- Zonguldak, TURKEY

Volume

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Start Page

1681

End Page

1683
Page Views

8

checked on Feb 24, 2026

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