Covariance Features for Trajectory Analysis
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Date
2016
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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
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Keywords
Trajectory Classification, Dynamic Time Warping, Clustering
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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
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1683
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