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Human action concentric video retrieval system using features weight updating method as relevance feedback

Retrieving videos based on its contents is becoming an increasingly popular area of research, because of enormous growth in the availability of multimedia information on public databases like Google and YouTube. Usually videos contain large variety of data but majority of online videos contain human...

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Main Authors: Rashid, Munaf, Abu-Bakar, S. A. R., Mokji, Musa, Abdu, Aliyu
Format: Conference or Workshop Item
Published: 2012
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://eprints.utm.my/id/eprint/51101/
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spelling my.utm.511012017-07-26T06:43:25Z http://eprints.utm.my/id/eprint/51101/ Human action concentric video retrieval system using features weight updating method as relevance feedback Rashid, Munaf Abu-Bakar, S. A. R. Mokji, Musa Abdu, Aliyu TK Electrical engineering. Electronics Nuclear engineering Retrieving videos based on its contents is becoming an increasingly popular area of research, because of enormous growth in the availability of multimedia information on public databases like Google and YouTube. Usually videos contain large variety of data but majority of online videos contain human as a subject of interest. In this paper, a human action based video retrieval system is presented which can be used to retrieve videos based on the contents of the query. The proposed system can search videos containing particular action on large databases efficiently. Furthermore, it is also shown that by using features weight updating approach as a Relevance feedback (RF), it is possible to involve user concepts interactively so that complex human action queries can be searched quickly to achieve useful results. Three popular Human action datasets namely Weizmann, KTH and UCF (sports) have been utilized in order to validate the performance of the proposed system. Experimental results and simulations show the efficacy of the proposed system. Even with number of visual challenges proposed approach will manage to get better accuracy as compare to other existing methods. 2012 Conference or Workshop Item PeerReviewed Rashid, Munaf and Abu-Bakar, S. A. R. and Mokji, Musa and Abdu, Aliyu (2012) Human action concentric video retrieval system using features weight updating method as relevance feedback. In: IEEE International Conference on Control System, Computing and Engineering (ICCSCE), NOV 23-25, 2011, Penang, Malaysia. http://apps.webofknowledge.com.ezproxy.utm.my/full_record.do?product=WOS&search_mode=GeneralSearch&qid=2&SID=P2dKpOzjmfD1umNCwlD&page=1&doc=1
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Rashid, Munaf
Abu-Bakar, S. A. R.
Mokji, Musa
Abdu, Aliyu
Human action concentric video retrieval system using features weight updating method as relevance feedback
description Retrieving videos based on its contents is becoming an increasingly popular area of research, because of enormous growth in the availability of multimedia information on public databases like Google and YouTube. Usually videos contain large variety of data but majority of online videos contain human as a subject of interest. In this paper, a human action based video retrieval system is presented which can be used to retrieve videos based on the contents of the query. The proposed system can search videos containing particular action on large databases efficiently. Furthermore, it is also shown that by using features weight updating approach as a Relevance feedback (RF), it is possible to involve user concepts interactively so that complex human action queries can be searched quickly to achieve useful results. Three popular Human action datasets namely Weizmann, KTH and UCF (sports) have been utilized in order to validate the performance of the proposed system. Experimental results and simulations show the efficacy of the proposed system. Even with number of visual challenges proposed approach will manage to get better accuracy as compare to other existing methods.
format Conference or Workshop Item
author Rashid, Munaf
Abu-Bakar, S. A. R.
Mokji, Musa
Abdu, Aliyu
author_facet Rashid, Munaf
Abu-Bakar, S. A. R.
Mokji, Musa
Abdu, Aliyu
author_sort Rashid, Munaf
title Human action concentric video retrieval system using features weight updating method as relevance feedback
title_short Human action concentric video retrieval system using features weight updating method as relevance feedback
title_full Human action concentric video retrieval system using features weight updating method as relevance feedback
title_fullStr Human action concentric video retrieval system using features weight updating method as relevance feedback
title_full_unstemmed Human action concentric video retrieval system using features weight updating method as relevance feedback
title_sort human action concentric video retrieval system using features weight updating method as relevance feedback
publishDate 2012
url http://eprints.utm.my/id/eprint/51101/
http://apps.webofknowledge.com.ezproxy.utm.my/full_record.do?product=WOS&search_mode=GeneralSearch&qid=2&SID=P2dKpOzjmfD1umNCwlD&page=1&doc=1
_version_ 1643652939294703616
score 13.211869

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