Robust Abnormal Event Recognition via Motion and Shape Analysis at ATM Installations
Joint Authors
Tripathi, Vikas
Gangodkar, Durgaprasad
Latta, Vivek
Mittal, Ankush
Source
Journal of Electrical and Computer Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-02-16
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Information Technology and Computer Science
Abstract EN
Automated teller machines (ATM) are widely being used to carry out banking transactions and are becoming one of the necessities of everyday life.
ATMs facilitate withdrawal, deposit, and transfer of money from one account to another round the clock.
However, this convenience is marred by criminal activities like money snatching and attack on customers, which are increasingly affecting the security of bank customers.
In this paper, we propose a video based framework that efficiently identifies abnormal activities happening at the ATM installations and generates an alarm during any untoward incidence.
The proposedapproach makes use of motion history image (MHI) and Hu moments to extract relevant features from video.
Principle component analysis has been used to reduce the dimensionality of features and classification hasbeen carried out by using support vector machine.
Analysis has been carried out on different video sequences by varying the window size of MHI.
The proposed framework is able to distinguish the normal andabnormal activities like money snatching, harm to the customer by virtue of fight, or attack on the customer with an average accuracy of 95.73%.
American Psychological Association (APA)
Tripathi, Vikas& Gangodkar, Durgaprasad& Latta, Vivek& Mittal, Ankush. 2015. Robust Abnormal Event Recognition via Motion and Shape Analysis at ATM Installations. Journal of Electrical and Computer Engineering،Vol. 2015, no. 2015, pp.1-10.
https://search.emarefa.net/detail/BIM-1068123
Modern Language Association (MLA)
Tripathi, Vikas…[et al.]. Robust Abnormal Event Recognition via Motion and Shape Analysis at ATM Installations. Journal of Electrical and Computer Engineering No. 2015 (2015), pp.1-10.
https://search.emarefa.net/detail/BIM-1068123
American Medical Association (AMA)
Tripathi, Vikas& Gangodkar, Durgaprasad& Latta, Vivek& Mittal, Ankush. Robust Abnormal Event Recognition via Motion and Shape Analysis at ATM Installations. Journal of Electrical and Computer Engineering. 2015. Vol. 2015, no. 2015, pp.1-10.
https://search.emarefa.net/detail/BIM-1068123
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1068123