Multimodal video analysis for crowd anomaly detection using open access tourism cameras
CoRR(2024)
摘要
In this article, we propose the detection of crowd anomalies through the
extraction of information in the form of time series from video format using a
multimodal approach. Through pattern recognition algorithms and segmentation,
informative measures of the number of people and image occupancy are extracted
at regular intervals, which are then analyzed to obtain trends and anomalous
behaviors. Specifically, through temporal decomposition and residual analysis,
intervals or specific situations of unusual behaviors are identified, which can
be used in decision-making and improvement of actions in sectors related to
human movement such as tourism or security.
The application of this methodology on the webcam of Turisme Comunitat
Valenciana in the town of Morella (Comunitat Valenciana, Spain) has provided
excellent results. It is shown to correctly detect specific anomalous
situations and unusual overall increases during the previous weekend and during
the festivities in October 2023. These results have been obtained while
preserving the confidentiality of individuals at all times by using measures
that maximize anonymity, without trajectory recording or person recognition.
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