Paper Info
Title
Strong, Neutral, or Weak: Exploring the Impostor Score Distribution
Abstract
The strong, neutral, or weak (SNoW) face impostor pairs problem is intended to explore the causes and impact of impostor face pairs that are inherently strong (easily recognized as nonmatches) or weak (possible false matches). The SNoW technique develops three partitions within the impostor score distribution of a given data set. Results provide evidence that varying degrees of impostor scores impact the overall performance of a face recognition system. This paper extends our earlier work to incorporate improvements regarding outlier detection for partitioning, explores the SNoW concept for the additional modalities of fingerprint and iris, and presents methods for how to begin to reveal the causes of weak impostor pairs. We also show a clear operational difference between strong and weak comparisons as well as identify partition stability across multiple algorithms.
Year
DOI
Venue
2015
10.1109/TIFS.2015.2403136
Information Forensics and Security, IEEE Transactions  
Keywords
Field
DocType
biometrics,face recognition,fingerprint recognition,iris recognition,performance evaluation,algorithm design and analysis,face,snow,fingerprint identification
Modalities,Anomaly detection,Facial recognition system,Algorithm design,Pattern recognition,Three-dimensional face recognition,Computer science,Fingerprint,Speech recognition,Artificial intelligence
Journal
Volume
Issue
ISSN
10
6
1556-6013
Citations 
PageRank 
References 
0
0.34
16
Authors
4
Name
Order
Citations
PageRank
Amanda Sgroi1434.58
Patrick J. Flynn24405307.04
Kevin W. Bowyer311121734.33
P. Jonathon Phillips49209801.62