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Iris Liveness Detection Competition (LivDet-Iris) -- The 2020 Edition
Priyanka Das, Joseph McGrath, Zhaoyuan Fang +20
Launched in 2013, LivDet-Iris is an international competition series open to academia and industry with the aim to assess and report advances in iris Presentation Attack Detection…
Is Face Recognition Sexist? No, Gendered Hairstyles and Biology Are
Vítor Albiero, Kevin W. Bowyer
Recent news articles have accused face recognition of being "biased", "sexist" or "racist". There is consensus in the research literature that face recognition accuracy is lower fo…
Iris Presentation Attack Detection: Where Are We Now?
Aidan Boyd, Zhaoyuan Fang, Adam Czajka +1
As the popularity of iris recognition systems increases, the importance of effective security measures against presentation attacks becomes paramount. This work presents an overvie…
The Criminality From Face Illusion
Kevin W. Bowyer, Michael King, Walter Scheirer +1
The automatic analysis of face images can generate predictions about a person's gender, age, race, facial expression, body mass index, and various other indices and conditions. A f…
A Method for Curation of Web-Scraped Face Image Datasets
Kai Zhang, Vítor Albiero, Kevin W. Bowyer
Web-scraped, in-the-wild datasets have become the norm in face recognition research. The numbers of subjects and images acquired in web-scraped datasets are usually very large, wit…
Are Gabor Kernels Optimal for Iris Recognition?
Aidan Boyd, Adam Czajka, Kevin Bowyer
Gabor kernels are widely accepted as dominant filters for iris recognition. In this work we investigate, given the current interest in neural networks, if Gabor kernels are the onl…
Deep Learning-Based Feature Extraction in Iris Recognition: Use Existing Models, Fine-tune or Train From Scratch?
Aidan Boyd, Adam Czajka, Kevin Bowyer
Modern deep learning techniques can be employed to generate effective feature extractors for the task of iris recognition. The question arises: should we train such structures from…
Robust Iris Presentation Attack Detection Fusing 2D and 3D Information
Zhaoyuan Fang, Adam Czajka, Kevin W. Bowyer
Diversity and unpredictability of artifacts potentially presented to an iris sensor calls for presentation attack detection methods that are agnostic to specificity of presentation…
How Does Gender Balance In Training Data Affect Face Recognition Accuracy?
Vítor Albiero, Kai Zhang, Kevin W. Bowyer
Deep learning methods have greatly increased the accuracy of face recognition, but an old problem still persists: accuracy is usually higher for men than women. It is often specula…
Analysis of Gender Inequality In Face Recognition Accuracy
Vítor Albiero, Krishnapriya K. S., Kushal Vangara +3
We present a comprehensive analysis of how and why face recognition accuracy differs between men and women. We show that accuracy is lower for women due to the combination of (1) t…
Learning Transformation-Aware Embeddings for Image Forensics
Aparna Bharati, Daniel Moreira, Patrick Flynn +3
A dramatic rise in the flow of manipulated image content on the Internet has led to an aggressive response from the media forensics research community. New efforts have incorporate…