NDLI: Integrating Visual and Textual Features for Web Image Clustering

Content Provider	IEEE Xplore Digital Library
Author	Xia, D.S. Xiang, Z.Q. Zou, Y.X.
Copyright Year	2015
Description	Author affiliation: ADSPLAB, Peking Univ., Shenzhen, China (Xia, D.S.; Xiang, Z.Q.; Zou, Y.X.)
Abstract	With the explosive growth of Web and tremendous development of digital image processing technologies, the applications of Web image have attracted much attention, such as the Web image retrieval. Since the Web images are often with some related text tags, making use of both visual and textual features of Web image will help improving the accuracy of the Web image clustering. Researches show that Web image clustering methods, such as graph partitioning models and hyper graph partitioning models, didn't make use the relations between texts and image simultaneously. In this paper, we explore to take both visual and textual features into account for Web image clustering by building a graph model and develop a novel iterative clustering method. With K clusters initialized, we calculate the occurrence frequency of each visual/textual feature over the j-th cluster (j = 1, 2,⋯, K), which is used to measure the significance of the feature for the j-th cluster. Then the likelihood of each image, which belongs to the j-th cluster, can be determined accordingly. Furthermore, a mixture model is built for the predicted feature linked to each image and the EM algorithm is adopted to get K component parameters which describe posterior probabilities of all clusters for each image. Then two K-dimensional vectors consisting of component parameters will be used to describe the image and adjust the cluster index of it. Several experiments have been performed with MIR-Flickr25K and IAPR TC-12 Benchmark datasets and the performance of the proposed Web image clustering algorithm is superior to that of the compared algorithm.
Starting Page	116
Ending Page	123
File Size	647458
Page Count	8
File Format	PDF
e-ISBN	9781479986880
DOI	10.1109/BigMM.2015.35
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-04-20
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Visualization Web image clustering Semantics Clustering algorithms Mixtual model Feature extraction Visual and textual features Multimedia communication Time complexity Ranking functions
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

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