NDLI: Compact Global Descriptors for Visual Search

Content Provider	IEEE Xplore Digital Library
Author	Chandrasekhar, V. Jie Lin Morere, O. Veillard, A. Goh, H.
Copyright Year	2015
Description	Author affiliation: Inst. for Infocomm Res., Singapore, Singapore (Chandrasekhar, V.; Jie Lin; Morere, O.; Goh, H.) \|\| Univ. Pierre et Marie Curie, Paris, France (Veillard, A.)
Abstract	The first step in an image retrieval pipeline consists of comparing global descriptors from a large database to find a short list of candidate matching images. The more compact the global descriptor, the faster the descriptors can be compared for matching. State-of-the-art global descriptors based on Fisher Vectors are represented with tens of thousands of floating point numbers. While there is significant work on compression of local descriptors, there is relatively little work on compression of high dimensional Fisher Vectors. We study the problem of global descriptor compression in the context of image retrieval, focusing on extremely compact binary representations: 64-1024 bits. Motivated by the remarkable success of deep neural networks in recent literature, we propose a compression scheme based on deeply stacked Restricted Boltzmann Machines (SRBM), which learn lower dimensional non-linear subspaces on which the data lie. We provide a thorough evaluation of several state-of-the-art compression schemes based on PCA, Locality Sensitive Hashing, Product Quantization and greedy bit selection, and show that the proposed compression scheme outperforms all existing schemes.
Starting Page	333
Ending Page	342
File Size	346804
Page Count	10
File Format	PDF
ISBN	9781479984305
ISSN	10680314
DOI	10.1109/DCC.2015.54
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-04-07
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image coding Training Transform coding Neural networks Principal component analysis Standards Visualization compact descriptors for visual search global descriptors feature compression
Content Type	Text
Resource Type	Article
Subject	Computer Networks and Communications

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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