75 citations · 147 across the 12 of their papers we have counts for
12 papers
Human-Machine Comparison for Cross-Race Face Verification: Race Bias at the Upper Limits of Performance?
Geraldine Jeckeln, Selin Yavuzcan, Kate A. Marquis +4
Face recognition algorithms perform more accurately than humans in some cases, though humans and machines both show race-based accuracy differences. As algorithms continue to impro…
Recognizing People by Body Shape Using Deep Networks of Images and Words
Blake A. Myers, Lucas Jaggernauth, Thomas M. Metz +4
Common and important applications of person identification occur at distances and viewpoints in which the face is not visible or is not sufficiently resolved to be useful. We exami…
Identity masking effectiveness and gesture recognition: Effects of eye enhancement in seeing through the mask
Madeline Rachow, Thomas Karnowski, Alice J. O'Toole
Face identity masking algorithms developed in recent years aim to protect the privacy of people in video recordings. These algorithms are designed to interfere with identification,…
Twin identification over viewpoint change: A deep convolutional neural network surpasses humans
Connor J. Parde, Virginia E. Strehle, Vivekjyoti Banerjee +4
Deep convolutional neural networks (DCNNs) have achieved human-level accuracy in face identification (Phillips et al., 2018), though it is unclear how accurately they discriminate…
The Influence of the Other-Race Effect on Susceptibility to Face Morphing Attacks
Snipta Mallick, Geraldine Jeckeln, Connor J. Parde +2
Facial morphs created between two identities resemble both of the faces used to create the morph. Consequently, humans and machines are prone to mistake morphs made from two identi…
A Study of the Human Perception of Synthetic Faces
Bingyu Shen, Brandon RichardWebster, Alice O'Toole +2
Advances in face synthesis have raised alarms about the deceptive use of synthetic faces. Can synthetic identities be effectively used to fool human observers? In this paper, we in…
Face Identification Proficiency Test Designed Using Item Response Theory
Géraldine Jeckeln, Ying Hu, Jacqueline G. Cavazos +5
Measures of face-identification proficiency are essential to ensure accurate and consistent performance by professional forensic face examiners and others who perform face-identifi…
Single Unit Status in Deep Convolutional Neural Network Codes for Face Identification: Sparseness Redefined
Connor J. Parde, Y. Ivette Colón, Matthew Q. Hill +3
Deep convolutional neural networks (DCNNs) trained for face identification develop representations that generalize over variable images, while retaining subject (e.g., gender) and…
Evaluating the Effectiveness of Automated Identity Masking (AIM) Methods with Human Perception and a Deep Convolutional Neural Network (CNN)
Kimberley D. Orsten-Hooge, Asal Baragchizadeh, Thomas P. Karnowski +5
Face de-identification algorithms have been developed in response to the prevalent use of public video recordings and surveillance cameras. Here, we evaluated the success of identi…
Deep Convolutional Neural Networks in the Face of Caricature: Identity and Image Revealed
Matthew Q. Hill, Connor J. Parde, Carlos D. Castillo +5
Real-world face recognition requires an ability to perceive the unique features of an individual face across multiple, variable images. The primate visual system solves the problem…
Face recognition assessments used in the study of super-recognisers
Eilidh Noyes, Alice J. O'Toole
The purpose of this paper is to provide a brief overview of nine assessments of face processing skills. These tests have been used commonly in recent years to gauge the skills of p…
Deep Convolutional Neural Network Features and the Original Image
Connor J. Parde, Carlos Castillo, Matthew Q. Hill +4
Face recognition algorithms based on deep convolutional neural networks (DCNNs) have made progress on the task of recognizing faces in unconstrained viewing conditions. These netwo…