NDLI: Optimizing Binary Fisher Codes for Visual Search

Content Provider	IEEE Xplore Digital Library
Author	Zhe Wang Ling-Yu Duan Jie Lin Jie Chen Tiejun Huang Wen Gao
Copyright Year	2015
Description	Author affiliation: Inst. of Digital Media, Peking Univ., Beijing, China (Zhe Wang; Ling-Yu Duan; Jie Lin; Jie Chen; Tiejun Huang; Wen Gao)
Abstract	Fisher vectors (FV) aggregated from local invariant features (e.g., SIFT) is one of the state-of-the-art descriptors for visual search, due to high discriminability but small visual vocabulary. Nevertheless, a high-dimensional FV needs to be compressed into a compact descriptor for light storage and high matching eficiency. In this paper, we formulate the FV compression as a resource-constrained optimization problem. Our goal is to maximize search performance subject to the constraints of descriptor compactness, compression complexity in terms of memory usage and time cost. Accordingly, we present a selective binary Fisher codes (SBFC) to compress the raw FV. Firstly, to fulfill the constraint of compression complexity, we binarize the FV by a sign function, Secondly, we propose to select discriminative bits from the binarized FV (BFC) to maximize search performance, subject to the constraint of descriptor compactness. Extensive experiments over MPEG Compact Descriptor for Visual Search (CDVS) benchmark datasets have shown that S-BFC significantly improves search performance at a smaller descriptor size as well as much lower complexity, compared with the state-of-the-art FV compression algorithms like Hashing and Product Quantziation (PQ). A simplified version of SBFC, SBFC LS has been adopted by the MPEG CDVS standard. In the CDVS evaluation framework, SBFC LS has achieved promising performance mean Average Precision (mAP) 83% on average at much lower memory cost of 40KB.
Starting Page	475
Ending Page	475
File Size	104504
Page Count	1
File Format	PDF
ISBN	9781479984305
ISSN	10680314
DOI	10.1109/DCC.2015.71
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	Visualization Complexity theory Bismuth Accuracy Entropy Transform coding Memory management
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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