NDLI: Transductive multi-distance learning for video search

Content Provider	Springer Nature Link
Author	Zhu, Songhao Liang, Zhiwei Liu, Yuncai
Copyright Year	2010
Abstract	Graph-based semi-supervised learning approaches have been proven effective and efficient in solving the problem of the inefficiency of labeled training data in many real-world application areas, such as video annotation. As a significant factor of these algorithms, however, pair-wise similarity metric of samples has not been fully investigated. Specifically, for existing approaches, the estimation of pair-wise similarity between two samples relies on the spatial property of video data. On the other hand, temporal property, an essential characteristic of video data, is not embedded into the pair-wise similarity measure. Accordingly, in this paper, a novel framework for video annotation, called Joint Spatio-Temporal Correlation Learning (JSTCL) is proposed. This framework is characterized by simultaneously taking into account both the spatial and temporal property of video data to improve the estimation of pair-wise similarity. We apply the proposed framework to video annotation and report superior performance compared to key existing approaches over the benchmark TRECVID data set.
Starting Page	117
Ending Page	124
Page Count	8
File Format	PDF
ISSN	14337541
Journal	Pattern Analysis & Applications
Volume Number	16
Issue Number	1
e-ISSN	1433755X
Language	English
Publisher	Springer-Verlag
Publisher Date	2011-01-01
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Graph-based semi-supervised learning Pair-wise similarity measure Spatio-temporal correlation Pattern Recognition
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Computer Vision and Pattern Recognition

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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
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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
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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