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

Content Provider	IEEE Xplore Digital Library
Author	Rashid, M. Abu-Bakar, S.A.R. Mokji, M. Abdu, A.
Copyright Year	2012
Description	Author affiliation: Micro Electronics and Computer Engineering Department Computer Vision Videos and image processing lab (CVVIP) Universiti Teknologi Malaysia UTM Johor Bahru, Skudai, Malaysia (Rashid, M.; Abu-Bakar, S.A.R.; Mokji, M.; Abdu, A.)
Abstract	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.
Starting Page	366
Ending Page	370
File Size	841379
Page Count	5
File Format	PDF
ISBN	9781467331425
e-ISBN	9781467331432
DOI	10.1109/ICCSCE.2012.6487172
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-11-23
Publisher Place	Malaysia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Interest pointst Bag of words (BOW) Relevance feedback (RF) Videos retrieval
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Action recognition using hybrid spatio-temporal bag-of-features

Content Based Image Retrieval and Classification using speeded-up robust features (SURF) and grouped bag-of-visual-words (GBoVW)

Video shots retrieval using local invariant features

Words-of-interest selection based on temporal motion coherence for video retrieval

A Multi-Scale Hierarchical Codebook Method for Human Action Recognition in Videos Using a Single Example

Video retrieval based on words-of-interest selection.

Text Retrieval Relevance Feedback Techniques for Bag of Words Model in CBIR

A Relevance Feedback Technique for Multimodal Retrieval of News Videos

Bag-of-visual-words expansion using visual relatedness for video indexing, SIGIR ’08 (2008)

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

Similar Documents

Action recognition using hybrid spatio-temporal bag-of-features

Content Based Image Retrieval and Classification using speeded-up robust features (SURF) and grouped bag-of-visual-words (GBoVW)

Video shots retrieval using local invariant features

Words-of-interest selection based on temporal motion coherence for video retrieval

A Multi-Scale Hierarchical Codebook Method for Human Action Recognition in Videos Using a Single Example

Video retrieval based on words-of-interest selection.

Text Retrieval Relevance Feedback Techniques for Bag of Words Model in CBIR

A Relevance Feedback Technique for Multimodal Retrieval of News Videos

Bag-of-visual-words expansion using visual relatedness for video indexing, SIGIR ’08 (2008)

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