Detecting Location-Based User Actions

The use of mobile devices with GPS facility is increasing in daily life. In this paper, we propose to detect several user actions based on data collected by the Mopsi application. We distinguish several types of actions such as: taking or uploading photos, completing tracking, visiting or passing-by a service and multiple users meeting. We evaluate the proposed algorithms by collecting ground truth and measuring error rates. The proposed methods perform with an average error of 5.9% and a weighted average error (WA) of 2.8%

Is Medoid Suitable for Averaging GPS Trajectories?

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

Roundness Measure for GPS Routes

We introduce a method to measure roundness of a GPS route. The method is compared to two existing roundness measure and is shown to outperform them in the presence of GPS noise. Our application is recreation outdoor game where players compete who can create roundest route