2026-06-01T22:05:25Zhttps://riuma.uma.es/rest/oai/request

oai:riuma.uma.es:10630/243532026-02-03T11:48:42Zcom_10630_2254col_10630_37959

Anomalous trajectory detection for automated traffic video surveillance Fernández-Rodríguez, Jose David García-González, Jorge Benítez-Rochel, Rafaela Molina-Cabello, Miguel Ángel López-Rubio, Ezequiel García-González, Jorge Diseño orientado a objetos Videovigilancia electrónica Visión artificial (Robótica) 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. 2022-06-13T11:12:23Z 2022-06-13T11:12:23Z 2022-06-13 2022 conference output https://hdl.handle.net/10630/24353 eng International Work-Conference on the Interplay between Natural and Artificial Computation Puerto de la Cruz, Tenerife, España 31 mayo 2022 open access