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Open AccessArticle

Estimating Road Segments Using Kernelized Averaging of GPS Trajectories

IRISA, Université Bretagne Sud, 35000 Rennes, France
Appl. Sci. 2019, 9(13), 2736; https://doi.org/10.3390/app9132736
Received: 28 May 2019 / Revised: 3 July 2019 / Accepted: 3 July 2019 / Published: 6 July 2019
(This article belongs to the Special Issue Averaging GPS Segments)
A method called iTEKA, which stands for iterative time elastic kernel averaging, was successfully used for averaging time series. In this paper, we adapt it to GPS trajectories. The key contribution is a denoising procedure that includes an over-sampling scheme, the detection and removal of outlier trajectories, a kernelized time elastic averaging method, and a down-sampling as post-processing. The experiment carried out on benchmark datasets showed that the proposed procedure is effective and outperforms straightforward methods based on medoid or Euclidean averaging approaches. View Full-Text
Keywords: GPS trajectory; time series averaging; noise reduction; kernel methods; dynamic time warping GPS trajectory; time series averaging; noise reduction; kernel methods; dynamic time warping
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Marteau, P.-F. Estimating Road Segments Using Kernelized Averaging of GPS Trajectories. Appl. Sci. 2019, 9, 2736.

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