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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/5620
Title: Surveillance scene representation and trajectory abnormality detection using aggregation of multiple concepts
Authors: Ahmed S.A.
Dogra D.P.
Kar S.
Pratim Roy, Partha
Published in: Expert Systems with Applications
Abstract: Use of CCTV is growing rapidly in surveillance applications. Rapid advancement in machine learning and camera hardware has opened-up adequate scopes to build next generation of expert systems aiming at understanding surveillance environments automatically by detection of trajectory abnormality through analyzing object behavior. Such intelligent surveillance systems should be able to learn and combine multiple concepts of abnormality in real-life scenario and classify the events of interest as normal or abnormal. Primary challenges of such systems are to represent and learn patterns in surveillance scenes and combine multiple concepts of abnormalities to activate the alarm system. This paper presents a graph-based representation of a given surveillance scene and learning of relevant features including origin, destination, path, speed, size, etc. These features are combined and correlated with target behaviors to detect abnormalities in moving object trajectories. We also propose an aggregation method that reduces the number of missed alarms during aggregation. Several cases using publicly available surveillance video datasets have been presented and the results indicate that the proposed method can be useful to design intelligent and expert surveillance systems. © 2018 Elsevier Ltd
Citation: Expert Systems with Applications (2018), 101(): 43-55
URI: https://doi.org/10.1016/j.eswa.2018.02.013
http://repository.iitr.ac.in/handle/123456789/5620
Issue Date: 2018
Publisher: Elsevier Ltd
Keywords: Aggregation of concepts
Multi parameter fusion
Trajectory abnormalities detection
Trajectory analysis
Visual surveillance
ISSN: 9574174
Author Scopus IDs: 57190343458
35408975400
55808071612
56880478500
Author Affiliations: Ahmed, S.A., Department of Mathematics, National Institute of Technology Durgapur, Durgapur, 713209, India
Dogra, D.P., School of Electrical Science, Indian Institute of Technology Bhubaneswar, Bhubaneswar, 751013, India
Kar, S., Department of Mathematics, National Institute of Technology Durgapur, Durgapur, 713209, India
Roy, P.P., Department of Computer Science and Engineering, Indian Institute of Technology Roorkee, Roorkee, 247667, India
Corresponding Author: Ahmed, S.A.; Department of Mathematics, National Institute of Technology DurgapurIndia; email: arif.1984.in@ieee.org
Appears in Collections:Journal Publications [CS]

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