A crowd video retrieval framework using generic descriptors

In the era of data mining and analytics, retrieval of crowd video with desired motion pattern segmentation plays a significant role in surveillance video management. The retrieval of crowd video with desired motion pattern segmentation poses challenges in finding generic descriptors to describe cro...

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Main Authors: Wong, Pei Voon, Mustapha, Norwati, Affendey, Lilly Suriani, Khalid, Fatimah
Format: Article
Language:English
Published: Academy Publisher 2020
Online Access:http://psasir.upm.edu.my/id/eprint/87590/
http://psasir.upm.edu.my/id/eprint/87590/1/ABSTRACT.pdf
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author Wong, Pei Voon
Mustapha, Norwati
Affendey, Lilly Suriani
Khalid, Fatimah
author_facet Wong, Pei Voon
Mustapha, Norwati
Affendey, Lilly Suriani
Khalid, Fatimah
author_sort Wong, Pei Voon
building UPM Institutional Repository
collection Online Access
description In the era of data mining and analytics, retrieval of crowd video with desired motion pattern segmentation plays a significant role in surveillance video management. The retrieval of crowd video with desired motion pattern segmentation poses challenges in finding generic descriptors to describe crowd patterns and similarity matching. This paper presents a novel crowd video retrieval framework using generic descriptors to overcome the above challenges. The anticipated structure comprises of four core components, namely motion feature extraction, group detection, learning generic descriptors, and crowd video retrieval. Results obtained indicate that the proposed framework can improve performance of crowd video retrieval compared with the existing crowd motions on CUHK Crowd Dataset.
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institution Universiti Putra Malaysia
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language English
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publishDate 2020
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spelling upm-875902022-07-06T07:49:43Z http://psasir.upm.edu.my/id/eprint/87590/ A crowd video retrieval framework using generic descriptors Wong, Pei Voon Mustapha, Norwati Affendey, Lilly Suriani Khalid, Fatimah In the era of data mining and analytics, retrieval of crowd video with desired motion pattern segmentation plays a significant role in surveillance video management. The retrieval of crowd video with desired motion pattern segmentation poses challenges in finding generic descriptors to describe crowd patterns and similarity matching. This paper presents a novel crowd video retrieval framework using generic descriptors to overcome the above challenges. The anticipated structure comprises of four core components, namely motion feature extraction, group detection, learning generic descriptors, and crowd video retrieval. Results obtained indicate that the proposed framework can improve performance of crowd video retrieval compared with the existing crowd motions on CUHK Crowd Dataset. Academy Publisher 2020 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/87590/1/ABSTRACT.pdf Wong, Pei Voon and Mustapha, Norwati and Affendey, Lilly Suriani and Khalid, Fatimah (2020) A crowd video retrieval framework using generic descriptors. Journal of Computers, 31 (1). 34 - 45. ISSN 1796-203X http://www.csroc.org.tw/journal/ 10.3966/199115992020023101003
spellingShingle Wong, Pei Voon
Mustapha, Norwati
Affendey, Lilly Suriani
Khalid, Fatimah
A crowd video retrieval framework using generic descriptors
title A crowd video retrieval framework using generic descriptors
title_full A crowd video retrieval framework using generic descriptors
title_fullStr A crowd video retrieval framework using generic descriptors
title_full_unstemmed A crowd video retrieval framework using generic descriptors
title_short A crowd video retrieval framework using generic descriptors
title_sort crowd video retrieval framework using generic descriptors
url http://psasir.upm.edu.my/id/eprint/87590/
http://psasir.upm.edu.my/id/eprint/87590/
http://psasir.upm.edu.my/id/eprint/87590/
http://psasir.upm.edu.my/id/eprint/87590/1/ABSTRACT.pdf