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
收藏
页码：671 / 682
页数：12
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