Is Medoid Suitable for Averaging GPS Trajectories?

ISPRS International Journal of Geo-Information

Biliaminu Jimoh¹  Radu Mariescu-Istodor¹  Pasi Fränti¹ 

[1] School of Computing, University of Eastern Finland, 80101 Joensuu, Finland;

关键词: medoid;    GPS trajectories;    segment averaging;    sequence averaging;    HC-SIM;    outliers;   

DOI  :  10.3390/ijgi11020133

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown