Paper Info
Title
Infant-ID: Fingerprints for Global Good
Abstract
In many of the least developed and developing countries, a multitude of infants continue to suffer and die from vaccine-preventable diseases and malnutrition. Lamentably, the lack of official identification documentation makes it exceedingly difficult to track which infants have been vaccinated and which infants have received nutritional supplements. Answering these questions could prevent this infant suffering and premature death around the world. To that end, we propose Infant-Prints, an end-to-end, low-cost, infant fingerprint recognition system. Infant-Prints is comprised of our (i) custom built, compact, low-cost (85 USD), high-resolution (1,900 ppi), ergonomic fingerprint reader, and (ii) high-resolution infant fingerprint matcher. To evaluate the efficacy of Infant-Prints, we collected a longitudinal infant fingerprint database captured in four different sessions over a 12-month time span (December 2018 to January 2020), from 315 infants at the Saran Ashram Hospital, a charitable hospital in Dayalbagh, Agra, India. Our experimental results demonstrate, for the first time, that Infant-Prints can deliver accurate and reliable recognition (over time) of infants enrolled between the ages of 2-3 months, in time for effective delivery of vaccinations, healthcare, and nutritional supplements ( <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">TAR = 95.2% @ FAR = 1.0%</b> for infants aged 8-16 weeks at enrollment and authenticated 3 months later). <xref ref-type="fn" rid="fn1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><sup>1</sup></xref> <fn id="fn1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><label>1.</label><p>A preliminary version of this paper was present at CVPRW Computer Vision for Global Challenges, Long Beach, CA, 2019.</p></fn>
Year
DOI
Venue
2022
10.1109/TPAMI.2021.3057634
IEEE Transactions on Pattern Analysis and Machine Intelligence
Keywords
DocType
Volume
Infant mortality,infantid,biometrics for global good,high resolution fingerprint reader,high resolution fingerprint matcher
Journal
44
Issue
ISSN
Citations 
7
0162-8828
2
PageRank 
References 
Authors
0.40
17
6
Name
Order
Citations
PageRank
Joshua J. Engelsma1225.78
Debayan Deb2647.25
Kai Cao320718.68
Anjoo Bhatnagar4192.60
Prem S. Sudhish520.40
Anil Jain6335073334.84