Loitering Detection Based on Pedestrian Activity Area Classification
Source abstract
Abstract
Loitering detection can help recognize vulnerable people needing attention and potential suspects harmful to public security. The existing loitering detection methods used time or target trajectories as assessment criteria, and only handled some simple loitering circumstances because of complex track. To solve these problems, this paper proposes a loitering detection method based on pedestrian activity area classification. The paper first gave loitering definition from a new perspective using the size of pedestrian activity area. The pedestrian loitering behaviors were divided into three categories. The proposed algorithms dynamically calculate enclosing rectangle, ellipse, and sector of pedestrian activity areas through curve fitting based on trajectory coordinates within given staying time threshold. The loitering is recognized if the pedestrian activity is detected to be constrained in an area within a certain period of time. The algorithm does not need to calculate complex trajectories. The PETS2007 dataset and our own self-collected simulated test videos were tested. The experimental results show that the proposed method accurately detected the pedestrian loitering, not only detected some loitering that the existing methods could not detect, but also distinguishing different types of loitering. The proposed method is effectiveness, robust, and simplified in implementation.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Anomaly Detection Techniques and Applications · Video Surveillance and Tracking Methods · Human Pose and Action Recognition
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Information Engineering, Nanchang University, Nanchang 330031, China
School of Software, Nanchang University, Nanchang 330047, China
Funding
National Natural Science Foundation of China · Natural Science Foundation of Jiangxi Province
References (55)
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