Proceedings ArticleDOI
A Survey and Analysis of Crowd Anomaly Detection Techniques
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TLDR
In this paper, the authors compared the merits and demerits of different methods for crowd anomaly detection in real time using various concepts and techniques such as AI, ML, optical flow analysis, streak flow analysis etc.Abstract:
In recent years, Crowd Anomaly detection has become a field of critical importance, especially so after the recent surge in technological development in the modern era An increasing number of situations or places require surveillance which is also required to detect anomalies so as to prevent unforeseen accidents Crowd Anomaly detection usually works by analyzing the surveillance scene in real time using various concepts and techniques such as AI, ML, optical flow analysis, streak flow analysis etc to identify anomalies in a crowd of people If an anomaly is found, the relevant authorities are immediately alerted In this survey paper, few of these methodologies are analyzed by comparing their merits and demeritsread more
Citations
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Journal ArticleDOI
Taxonomy of Anomaly Detection Techniques in Crowd Scenes
Amnah Aldayri,Waleed Albattah +1 more
TL;DR: A detailed review of the recent development of anomaly detection methods from the perspectives of computer vision on different available datasets is presented.
References
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Journal ArticleDOI
Abnormal Crowd Behavior Detection Using Motion Information Images and Convolutional Neural Networks
TL;DR: A novel method for abnormal crowd event detection in surveillance videos that focuses on panic and escape behavior detection that may appear because of violent events and natural disasters is introduced.
Journal ArticleDOI
Real-Time Crowd Monitoring Using Seamless Indoor-Outdoor Localization
TL;DR: A novel and real-time surveillance system (named, SmartISS) which identifies, tracks and monitors individuals’ wireless equipment(s) using their MAC ids and an algorithm to select the optimal number of PSUs for finding the latest location of the suspicious person(s).
Proceedings ArticleDOI
Deep Learning and One-class SVM based Anomalous Crowd Detection
TL;DR: A deep representation approach to the problem, which extracts and represents features in an unsupervised way and can detect anomalous activity like standing statically and loitering among a crowd of people is proposed.
Journal ArticleDOI
HUAD: Hierarchical Urban Anomaly Detection Based on Spatio-Temporal Data
TL;DR: The Hierarchical Urban Anomaly Detection (HUAD) framework is proposed, the effectiveness of the method is verified, and the traffic flow of the target region and adjacent regions is analyzed from multiple perspectives in view of the large crowd gathering activities.
Proceedings ArticleDOI
Abnormal Crowd Behavior Detection Based on Predictive Neural Network
TL;DR: The predictive neural network is innovatively applied to crowd anomaly detection by enlarging the differences between predictive frames and real frames in moving object regions by adjusting the threshold adaptively, and the abnormal behavior in the crowd can be judged.