NDLI: Graph-Based Hierarchical Video Summarization Using Global Descriptors

Content Provider	IEEE Xplore Digital Library
Author	Belo, L. Caetano, C. Patrocinio, Z. Guimaraes, S.
Copyright Year	2014
Description	Author affiliation: Comput. Sci. Dept. (DCC/ICEI), Pontificia Univ. Catolica de Minas Gerais (PUC Minas), Belo Horizonte, Brazil (Belo, L.; Caetano, C.; Patrocinio, Z.; Guimaraes, S.)
Abstract	Video summarization is a simplification of video content for compacting the video information. The video summarization problem can be transformed to a clustering problem, in which some frames are selected to saliently represent the video content. In this work, we use a hierarchical graph-based clustering method for computing a video summary. In fact, the proposed approach, called Summary, adopts a hierarchical clustering method to generate a weight map from the frame similarity graph in which the clusters (or connected components of the graph) can easily be inferred. Moreover, the use of this strategy allows to apply a similarity measure between clusters during graph partition, instead of considering only the similarity between isolated frames. Furthermore, a new evaluation measure that assesses the diversity of opinions of user summaries, called Covering, is also proposed. Experimental results provide quantitative and qualitative comparison between the new approach and other popular algorithms from the literature, showing that the new algorithm is robust and efficient. Concerning quality measures, Summary outperforms the compared methods regardless of the visual feature used in terms of F-measure.
Starting Page	822
Ending Page	829
File Size	1390732
Page Count	8
File Format	PDF
ISBN	9781479965724
ISSN	10823409
DOI	10.1109/ICTAI.2014.127
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-11-10
Publisher Place	Cyprus
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Clustering algorithms Clustering methods Histograms Merging Distortion measurement Visualization Indexes observation scales Graph-based hierarchical video summarization covering global descriptors
Content Type	Text
Resource Type	Article

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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
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