TS-SCAN: a Density-Based Clustering Method for Trajectory Analysis and Anomaly Detection

The surging amount of trajectories from sensors, antennas, and radars calls for the development of modern trajectory analysis techniques. In this context, we have introduced 2 ways to compare trajectories, which include a regularisation for dynamic time warping (DTW) and a faster computation of the Fréchet distance. As an example, we present TS-SCAN, an extension of the DBSCAN algorithm, which computes trajectory clusters and their average scheme in a database.

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Published
2024-10-21
DOI
https://doi.org/10.1109/radar58436.2024.10994148
Primary Topic
Anomaly Detection Techniques and Applications
Type
article
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article

TS-SCAN: a Density-Based Clustering Method for Trajectory Analysis and Anomaly Detection

Karim Tit, Louis‐Marie Traonouez, Léo Monnier
Anomaly Detection Techniques and Applications
article

TS-SCAN: a Density-Based Clustering Method for Trajectory Analysis and Anomaly Detection

Karim Tit, Louis‐Marie Traonouez, Léo Monnier
article en

Abstract

The surging amount of trajectories from sensors, antennas, and radars calls for the development of modern trajectory analysis techniques. In this context, we have introduced 2 ways to compare trajectories, which include a regularisation for dynamic time warping (DTW) and a faster computation of the Fréchet distance. As an example, we present TS-SCAN, an extension of the DBSCAN algorithm, which computes trajectory clusters and their average scheme in a database.

Université de Technologie de Troyes (FR), Centre Inria de l'Université de Rennes (FR), Thales (France) (FR)
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Anomaly Detection Techniques and Applications
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