Covariance Features for Trajectory Analysis
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Date
2016
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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
ORCID
Keywords
Trajectory Classification, Dynamic Time Warping, Clustering
Turkish CoHE Thesis Center URL
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24th Signal Processing and Communication Application Conference (SIU) -- MAY 16-19, 2016 -- Zonguldak, TURKEY
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Start Page
1681
End Page
1683
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