NDLI: Social Attribute-Aware Force Model: Exploiting Richness of Interaction for Abnormal Crowd Detection

Content Provider	IEEE Xplore Digital Library
Author	Yanhao Zhang Lei Qin Rongrong Ji Hongxun Yao Qingming Huang
Copyright Year	1991
Abstract	Interactions among pedestrians usually play an important role in understanding crowd behavior. However, there are great challenges, such as occlusions, motion, and appearance variance, on accurate analysis of pedestrian interactions. In this paper, we introduce a novel social attribute-aware force model (SAFM) for detection of abnormal crowd events. The proposed model incorporates social characteristics of crowd behaviors to improve the description of interactive behaviors. To this end, we first efficiently estimate the scene scale in an unsupervised manner. Then, we introduce the concepts of social disorder and congestion attributes to characterize the interaction of social behaviors, and construct our crowd interaction model on the basis of social force by an online fusion strategy. These attributes encode social interaction characteristics and offer robustness against motion pattern variance. Abnormal event detection is finally performed based on the proposed SAFM. In addition, the attribute-aware interaction force indicates the possible locations of anomalous interactions. We validate our method on the publicly available data sets for abnormal detection, and the experimental results show promising performance compared with alternative and state-of-the-art methods.
Sponsorship	IEEE Circuits and Systems Society
Starting Page	1231
Ending Page	1245
Page Count	15
File Size	4154551
File Format	PDF
ISSN	10518215
Volume Number	25
Issue Number	7
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Force Semantics Dynamics Hidden Markov models Analytical models Bayes methods Robustness social force model Abnormal detection crowd behaviors social attributes
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Media Technology

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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