Anomalous Trajectory Detection for Automated Traffic Video Surveillance
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Jose D. Fernández [1] ; Jorge García-González [1] ; Rafaela Benítez-Rochel [1] ; Miguel Molina-Cabello [1] ; Ezequiel López-Rubio [1]
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[1] Universidad de Málaga
Universidad de Málaga
Málaga, España
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- Localización: Bio-inspired Systems and Applications: from Robotics to Ambient Intelligence: 9th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2022, Puerto de la Cruz, Tenerife, Spain, May 31 – June 3, 2022, Proceedings, Part II / José Manuel Ferrández Vicente (dir. congr.), José Ramón Álvarez Sánchez (dir. congr.), Félix de la Paz López (dir. congr.), Hojjat Adeli (aut.), 2022, ISBN 978-3-031-06527-9, págs. 173-182
- Idioma: inglés
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Resumen
Vehicle trajectories extracted from traffic video sequences can be helpful for many purposes. In particular, the analysis of detected anomalous trajectories may enhance drivers’ safety. This work proposes a methodology to detect anomalous vehicle trajectories by using a vehicle detection, a vehicle tracking and a processing of the tracking information steps. Once trajectories are detected, their velocity vectors are estimated and an anomaly value is computed for each trajectory by comparing its vector with those from its nearest neighbours. The management of these anomaly values allows considering which trajectories are suitable to be potentially anomalous considered. Real and synthetic videos have been included in the experiments to perform the goodness of the proposal.
