Towards Abnormal Trajectory and Event Detection in Video Surveillance - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Article Dans Une Revue IEEE Transactions on Circuits and Systems for Video Technology Année : 2016

Towards Abnormal Trajectory and Event Detection in Video Surveillance

Résumé

In this paper we present a unified approach for abnormal behavior detection and group behavior analysis in video scenes. Existing approaches for abnormal behavior detection do either use trajectory based or pixel based methods. Unlike these approaches, we propose an integrated pipeline that incorporates the output of object trajectory analysis and pixel-based analysis for abnormal behavior inference. This enables to detect abnormal behaviors related to speed and direction of object trajectories, as well as complex behaviors related to finer motion of each object. By applying our approach on three different datasets, we show that our approach is able to detect several types of abnormal group behaviors with less number of false alarms compared to existing approaches.
Fichier principal
Vignette du fichier
SerhanTCSVT2016(1).pdf (7.69 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-01849787 , version 1 (26-07-2018)

Identifiants

  • HAL Id : hal-01849787 , version 1

Citer

Serhan Cosar, Giuseppe Donatiello, Vania Bogorny, Carolina Garate, Luis Otavio Alvares, et al.. Towards Abnormal Trajectory and Event Detection in Video Surveillance. IEEE Transactions on Circuits and Systems for Video Technology, 2016. ⟨hal-01849787⟩
106 Consultations
822 Téléchargements

Partager

Gmail Facebook X LinkedIn More