NDLI: Analysing comparative soft biometrics from crowdsourced annotations

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Analysing comparative soft biometrics from crowdsourced annotations

Content Provider	IET Digital Library
Author	Corbishley, Daniel Martinho Nixon, Mark S. Carter, John N.
Abstract	Soft biometrics enable human description and identification from low-quality surveillance footage. This study premises the design, collection and analysis of a novel crowdsourced dataset of comparative soft biometric body annotations, obtained from a richly diverse set of human annotators. The authors annotate 100 subject images to provide a coherent, in-depth appraisal of the collected annotations and inferred relative labels. The dataset includes gender as a comparative trait and the authors find that comparative labels characteristically contain additional discriminative information over traditional categorical annotations. Using the authors’ pragmatic dataset, semantic recognition is performed by inferring relative biometric signatures using a RankSVM algorithm. This demonstrates a practical scenario, reproducing responses from a video surveillance operator searching for an individual. The approach can reliably return the correct match in the top 7% of results with ten comparisons, or top 13% of results using just five sets of subject comparisons.
Starting Page	276
Ending Page	283
Page Count	8
ISSN	20474938
Volume Number	5
e-ISSN	20474946
Issue Number	Issue 4, Dec (2016)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-bmt/5/4
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-bmt.2015.0118
Journal	IET Biometrics
Publisher Date	2016-04-22
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Additional Discriminative Information Biomimetics Comparative Soft Biometric Analysis Comparative Soft Biometric Body Annotations Crowdsourced Annotations Data Security Human Description Human Identification Image Recognition Knowledge Engineering Technique Low-quality Surveillance Footage Pragmatic Dataset RankSVM Algorithm Semantic Recognition Support Vector Machine System And Application Television And Video Equipment Video Signal Processing Video Surveillance Video Surveillance Operator Searching
Content Type	Text
Resource Type	Article
Subject	Signal Processing Computer Vision and Pattern Recognition Software

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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