NDLI: Is Medoid Suitable for Averaging GPS Trajectories?

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Is Medoid Suitable for Averaging GPS Trajectories?

Content Provider	MDPI
Author	Pasi, Fränti Jimoh, Biliaminu Mariescu-Istodor, Radu
Copyright Year	2022
Description	Averaging GPS trajectories is needed in applications such as clustering and automatic extraction of road segments. Calculating mean for trajectories and other time series data is non-trivial and shown to be an NP-hard problem. medoid has therefore been widely used as a practical alternative and because of its (assumed) better noise tolerance. In this paper, we study the usefulness of the medoid to solve the averaging problem with ten different trajectory-similarity/-distance measures. Our results show that the accuracy of medoid depends mainly on the sample size. Compared to other averaging methods, the performance deteriorates especially when there are only few samples from which the medoid must be selected. Another weakness is that medoid inherits properties such as the sample frequency of the arbitrarily selected sample. The choice of the trajectory distance function becomes less significant. For practical applications, other averaging methods than medoid seem a better alternative for higher accuracy.
Starting Page	133
e-ISSN	22209964
DOI	10.3390/ijgi11020133
Journal	ISPRS International Journal of Geo-Information
Issue Number	2
Volume Number	11
Language	English
Publisher	MDPI
Publisher Date	2022-02-14
Access Restriction	Open
Subject Keyword	ISPRS International Journal of Geo-Information Isprs International Journal of Geo-information Industrial Engineering Medoid Gps Trajectories Segment Averaging Sequence Averaging Hc-sim Outliers
Content Type	Text
Resource Type	Article

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