NDLI: BioHDD: a dataset for studying biometric identification on heavily degraded data

Content Provider	IET Digital Library
Author	Santos, Gil Fiadeiro, Paulo T. Proença, Hugo
Abstract	Substantial efforts have been put into bridging the gap between biometrics and visual surveillance, in order to develop automata able to recognise human beings ‘in the wild’. This study focuses on biometric recognition in extremely degraded data, and its main contributions are three-fold: (1) announce the availability of an annotated dataset that contains high quality mugshots of 101 subjects, and large sets of probes degraded extremely by 10 different noise factors; (2) report the results of a mimicked watchlist identification scheme: an online survey was conducted, where participants were asked to perform positive and negative identification of probes against the enrolled identities. Along with their answers, volunteers had to provide the major reasons that sustained their responses, which enabled the authors to perceive the kind of features that are most frequently associated with successful/failed human identification processes. As main conclusions, the authors observed that humans rely greatly on shape information and holistic features. Otherwise, colour and texture-based features are almost disregarded by humans; (3) finally, the authors give evidence that the positive human identification on such extremely degraded data might be unreliable, whereas negative identification might constitute an interesting alternative for such cases.
Starting Page	1
Ending Page	9
Page Count	9
ISSN	20474938
Volume Number	4
e-ISSN	20474946
Issue Number	Issue 1, Mar (2015)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-bmt/4/1
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-bmt.2014.0045
Journal	IET Biometrics
Publisher Date	2015-01-19
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Annotated Dataset Automata BioHDD Biometric Identification Biometric Recognition Biomimetics Colour Based Feature Computer Vision And Image Processing Technique Enrolled Identity Heavily Degraded Data Human Identification Process Image Colour Analysis Image Recognition Image Texture Negative Identification Positive Identification Shape Information Texture-based Feature Video Signal Processing Video Surveillance Visual Surveillance Watchlist Identification Scheme
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
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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
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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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