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Title: Natural language description of surveillance events
Authors: Ahmed S.A.
Dogra D.P.
Kar S.
Pratim Roy, Partha
Li F.
Chandra P.
Giri D.
Jana D.K.
Kar S.
Published in: Proceedings of Advances in Intelligent Systems and Computing
Abstract: This paper presents a novel method to represent hours of surveillance video in a pattern-based text log. We present a tag and template-based technique that automatically generates natural language descriptions of surveillance events. We combine the output of some of the existing object tracker, deep learning guided object and action classifiers, and graph-based scene knowledge to assign hierarchical tags and generate natural language description of surveillance events. Unlike some state-of-the-art image and short video descriptor methods, our approach can describe videos, specifically surveillance videos by combining frame-level, temporal-level, and behavior-level target tags/features. We evaluate our method against two baseline video descriptors, and our analysis suggests that supervised scene knowledge and template can improve video descriptions, specially in surveillance videos. © 2019, Springer Nature Singapore Pte Ltd.
Citation: Proceedings of Advances in Intelligent Systems and Computing, (2019), 141- 151
Issue Date: 2019
Publisher: Springer Verlag
Keywords: Surveillance video description
Video description
Video to text
ISBN: 9.78981E+12
ISSN: 21945357
Author Scopus IDs: 57190343458
Author Affiliations: Ahmed, S.A., National Institute of Technology Durgapur, Durgapur, WB 713209, India
Dogra, D.P., Indian Institute of Technology Bhubaneswar, Bhubaneswar, Odisha 751013, India
Kar, S., National Institute of Technology Durgapur, Durgapur, WB 713209, India
Roy, P.P., Indian Institute of Technology Roorkee, Roorkee, Uttarakhand 247667, India
Corresponding Author: Ahmed, S.A.; National Institute of Technology DurgapurIndia; email:
Appears in Collections:Conference Publications [CS]

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