NDLI: Indexing heterogeneous features with superimages

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Indexing heterogeneous features with superimages

Content Provider	Springer Nature Link
Author	Gao, Wen Huang, Tiejun Tian, Qi Zhang, Shiliang Luo, Qingjun
Copyright Year	2014
Abstract	As an important procedure in image retrieval, off-line indexing focuses on organizing relevant images together and largely decides the efficiency, accuracy, and memory cost of the retrieval system. Because the image contains multi-level visual and semantic clues, the described indexing strategy should be able to reflect such multi-level relevance. However, most of the existing indexing strategies view database images individually and only consider partial relevance, i.e., relevance reflected by either local or global feature. To overcome these issues and design better indexing strategy, we propose to package semantically relevant images into superimages, and then index superimages instead of single images. Superimage effectively packages multiple images into one new unit, and hence significantly decreases the number of images to be indexed. This naturally saves the memory cost and retrieval time. To make the final index file discriminative to both visual and semantic relevances, we extract local descriptors from superimages and index them with inverted file. During online retrieval, we only need to extract local descriptors from queries, but could get semantic-aware retrieval results. This is because during our off-line indexing stage, both the semantically and visually relevant images are organized together by indexing heterogeneous features in superimages. Therefore, our approach is naturally superior to many online retrieval fusion algorithms in terms of retrieval efficiency and memory consumption. Moreover, extensive experiments on multiple retrieval tasks also manifest the promising accuracy of our approach.
Starting Page	245
Ending Page	257
Page Count	13
File Format	PDF
ISSN	21926611
Journal	International Journal of Multimedia Information Retrieval
Volume Number	3
Issue Number	4
e-ISSN	2192662X
Language	English
Publisher	Springer London
Publisher Date	2014-09-11
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Large-scale visual search Superimage Information Storage and Retrieval Data Mining and Knowledge Discovery Image Processing and Computer Vision Computer Science Semantic feature Information Systems Applications (incl. Internet) Multimedia Information Systems Image indexing
Content Type	Text
Resource Type	Article
Subject	Library and Information Sciences Information Systems Media Technology

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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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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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