Statistical Abnormal Crowd Behavior Detection and Simulation for Real-Time Applications

被引：9

作者：

Aguilar, Wilbert G. ^{[1
,4
,5
]}

Luna, Marco A. ^{[2
]}

Ruiz, Hugo ^{[1
,8
]}

Moya, Julio F. ^{[2
]}

Luna, Marco P. ^{[3
,7
]}

Abad, Vanessa ^{[6
]}

Parra, Humberto ^{[1
,7
]}

机构：

[1] Univ Fuerzas Armadas ESPE, Dept DECEM, Sangolqui, Ecuador

[2] Univ Fuerzas Armadas ESPE, Dept DEEE, Sangolqui, Ecuador

[3] Univ Fuerzas Armadas ESPE, Dept Tierra & Construcc, Sangolqui, Ecuador

[4] Univ Fuerzas Armadas ESPE, CICTE Res Ctr, Sangolqui, Ecuador

[5] Univ Politecn Cataluna, GREC Res Grp, Barcelona, Spain

[6] Univ Barcelona, Barcelona, Spain

[7] Purdue Univ, PLM Res Ctr, Indiana, PA USA

[8] Univ Politecn Madrid, Madrid, Spain

来源：

INTELLIGENT ROBOTICS AND APPLICATIONS, ICIRA 2017, PT II | 2017年 / 10463卷

关键词：

Abnormal crowd; Surveillance; Image analysis; Real-time applications; EVENT DETECTION; ANOMALY DETECTION; PATTERNS; SCENES;

D O I：

10.1007/978-3-319-65292-4_58

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper proposes a low computational cost method for abnormal crowd behavior detection with surveillance applications in fixed cameras. Our proposal is based on statistical modelling of moved pixels density. For modelling we take as reference datasets available in the literature focused in crowd behavior. During anomalous events we capture data to replicate abnormal crowd behavior for computer graphics and virtual reality applications. Our algorithm performance is compared with other proposals in the literature applied in two datasets. In addition, we test the execution time to validate its usage in real-time. In the results we obtain fast execution time of the algorithm and robustness in its performance.

引用

页码：671 / 682

页数：12

共 50 条

[31] Research on Abnormal Detection Technology of Real-time Interaction Process in New Energy Network [J].

Peng, Bo ;

Wang, Qi ;

Li, Xin ;

Cai, Junhui ;

Fei, Jiaxuan ;

Chen, Wei .

2019 INTERNATIONAL CONFERENCE ON INTERNET OF THINGS (ITHINGS) AND IEEE GREEN COMPUTING AND COMMUNICATIONS (GREENCOM) AND IEEE CYBER, PHYSICAL AND SOCIAL COMPUTING (CPSCOM) AND IEEE SMART DATA (SMARTDATA), 2019, :433-440

[32] LRATD: a lightweight real-time abnormal trajectory detection approach for road traffic surveillance [J].

Chun Zhang ;

Keyan Ren .

Neural Computing and Applications, 2022, 34 :22417-22434

[33] Reading Detection in Real-time [J].

Kelton, Conor ;

Wei, Zijun ;

Ahn, Seoyoung ;

Balasubramanian, Aruna ;

Das, Samir R. ;

Samaras, Dimitris ;

Zelinsky, Gregory .

ETRA 2019: 2019 ACM SYMPOSIUM ON EYE TRACKING RESEARCH & APPLICATIONS, 2019,

[34] Unusual Human Behavior Detection System in Real-Time Video Systems [J].

Bu, Yanbin ;

Chen, Ting ;

Duan, Hongxiu ;

Liu, Mei ;

Xue, Yandan .

INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2023, 14 (06) :970-979

[35] Real-time anomaly detection in elderly behavior with the support of task models [J].

Parvin, Parvaneh ;

Chessa, Stefano ;

Manca, Marco ;

Paternò, Fabio .

Proceedings of the ACM on Human-Computer Interaction, 2018, 2 (EICS)

[36] Abnormal Behavior Detection in Crowd Scene Using YOLO and Conv-AE [J].

Li Yajing ;

Dai Zhongjian .

PROCEEDINGS OF THE 33RD CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2021), 2021, :1720-1725

[37] Hybrid Histogram of Oriented Optical Flow for Abnormal Behavior Detection in Crowd Scenes [J].

Wang, Qiang ;

Ma, Qiao ;

Luo, Chao-Hui ;

Liu, Hai-Yan ;

Zhang, Can-Long .

INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, 2016, 30 (02)

[38] Real-Time Anomaly Detection Using Distributed Tracing in Microservice Cloud Applications [J].

Raeiszadeh, Mahsa ;

Ebrahimzadeh, Amin ;

Saleem, Ahsan ;

Glitho, Roch H. ;

Eker, Johan ;

Mini, Raquel A. F. .

2023 IEEE 12TH INTERNATIONAL CONFERENCE ON CLOUD NETWORKING, CLOUDNET, 2023, :36-44

[39] Asynchronous Real-Time Federated Learning for Anomaly Detection in Microservice Cloud Applications [J].

Raeiszadeh, Mahsa ;

Ebrahimzadeh, Amin ;

Glitho, Roch H. ;

Eker, Johan ;

Mini, Raquel A. F. .

IEEE TRANSACTIONS ON MACHINE LEARNING IN COMMUNICATIONS AND NETWORKING, 2025, 3 :176-194

[40] A Real-time Detection Scheme of User Behavior Anomaly for Management Information System [J].

Sun, Xiaohan ;

Yang, Guanghong ;

Zhang, Jilan .

PROCEEDINGS OF 2020 IEEE 4TH INFORMATION TECHNOLOGY, NETWORKING, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (ITNEC 2020), 2020, :1054-1058

← 1 2 3 4 5 →