Kevin W. Bowyer

Revisiting Face Recognition for Monozygotic Twins: The Celeb Twins Test Set

Michael Zang, Haiyu Wu, Mrinal Sharma +1

Past literature on face recognition for monozygotic (("identical") twins points to facial marks and mirror asymmetry as possible directions for improved accuracy of twins recogniti…

Rank-1 Identity Consensus Predicts Gallery Enrollment in 1:N Face Matching More Accurately than Score Thresholding

Gabriella Pangelinan, Aman Bhatta, Michael C. King +1

In operational 1:N face identification, a crucial question arises for each probe: is this person enrolled in the gallery or not? The stakes are high and asymmetric. Rejecting a mat…

What Happens to Accuracy When Photo Lineups Contain Non-Mated Rank-One Images From Large Galleries?

Genesis Argueta, Kevin W. Bowyer, Michael King +1

One-to-many facial identification is commonly used to match a probe image from surveillance video against a gallery of driver's license and/or booking photos. The algorithm's rank-…

Beyond Mortality: Advancements in Post-Mortem Iris Recognition through Data Collection and Computer-Aided Forensic Examination

Rasel Ahmed Bhuiyan, Parisa Farmanifard, Renu Sharma +7

Post-mortem iris recognition brings both hope to the forensic community (a short-term but accurate and fast means of verifying identity) as well as concerns to society (its potenti…

Diffusion for De-Occlusion: Accessory-Aware Diffusion Inpainting for Robust Ear Biometric Recognition

Deeksha Arun, Kevin W. Bowyer, Patrick Flynn

Ear occlusions (arising from the presence of ear accessories such as earrings and earphones) can negatively impact performance in ear-based biometric recognition systems, especiall…

PaW-ViT: A Patch-based Warping Vision Transformer for Robust Ear Verification

Deeksha Arun, Kevin W. Bowyer, Patrick Flynn

The rectangular tokens common to vision transformer methods for visual recognition can strongly affect performance of these methods due to incorporation of information outside the…

Restricted Receptive Fields for Face Verification

Kagan Ozturk, Aman Bhatta, Haiyu Wu +2

Understanding how deep neural networks make decisions is crucial for analyzing their behavior and diagnosing failure cases. In computer vision, a common approach to improve interpr…

How Does Bilateral Ear Symmetry Affect Deep Ear Features?

Kagan Ozturk, Deeksha Arun, Kevin W. Bowyer +1

Ear recognition has gained attention as a reliable biometric technique due to the distinctive characteristics of human ears. With the increasing availability of large-scale dataset…

Are you In or Out (of gallery)? Wisdom from the Same-Identity Crowd

Aman Bhatta, Maria Dhakal, Michael C. King +1

A central problem in one-to-many facial identification is that the person in the probe image may or may not have enrolled image(s) in the gallery; that is, may be In-gallery or Out…

Vec2Face+ for Face Dataset Generation

Haiyu Wu, Jaskirat Singh, Sicong Tian +2

When synthesizing identities as face recognition training data, it is generally believed that large inter-class separability and intra-class attribute variation are essential for s…

Deep CNN Face Matchers Inherently Support Revocable Biometric Templates

Aman Bhatta, Michael C. King, Kevin W. Bowyer

One common critique of biometric authentication is that if an individual's biometric is compromised, then the individual has no recourse. The concept of revocable biometrics was de…

Improved Ear Verification with Vision Transformers and Overlapping Patches

Deeksha Arun, Kagan Ozturk, Kevin W. Bowyer +1

Ear recognition has emerged as a promising biometric modality due to the relative stability in appearance during adulthood. Although Vision Transformers (ViTs) have been widely use…

Peepers & Pixels: Human Recognition Accuracy on Low Resolution Faces

Xavier Merino, Gabriella Pangelinan, Samuel Langborgh +2

Automated one-to-many (1:N) face recognition is a powerful investigative tool commonly used by law enforcement agencies. In this context, potential matches resulting from automated…

A Siamese Network to Detect If Two Iris Images Are Monozygotic

Yongle Yuan, Kevin W. Bowyer

This study presents the first automated classifier designed to determine whether a pair of iris images originates from monozygotic individuals, addressing a previously untackled pr…

Lights, Camera, Matching: The Role of Image Illumination in Fair Face Recognition

Gabriella Pangelinan, Grace Bezold, Haiyu Wu +2

Facial brightness is a key image quality factor impacting face recognition accuracy differentials across demographic groups. In this work, we aim to decrease the accuracy gap betwe…

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes

Paul Jonas Kurz, Haiyu Wu, Rouqaiah Al-Refai +2

Face recognition systems (FRS) exhibit significant accuracy differences based on the user's gender. Since such a gender gap reduces the trustworthiness of FRS, more recent efforts…

cs.CV2024★ 1 cited

Impact of Sunglasses on One-to-Many Facial Identification Accuracy

Sicong Tian, Haiyu Wu, Michael C. King +1

One-to-many facial identification is documented to achieve high accuracy in the case where both the probe and the gallery are "mugshot quality" images. However, an increasing numbe…

Training Better Deep Learning Models Using Human Saliency

Aidan Boyd, Patrick Tinsley, Kevin W. Bowyer +1

This work explores how human judgement about salient regions of an image can be introduced into deep convolutional neural network (DCNN) training. Traditionally, training of DCNNs…

Vec2Face: Scaling Face Dataset Generation with Loosely Constrained Vectors

Haiyu Wu, Jaskirat Singh, Sicong Tian +2

This paper studies how to synthesize face images of non-existent persons, to create a dataset that allows effective training of face recognition (FR) models. Besides generating rea…

cs.CV2024★ 1 cited

Can the accuracy bias by facial hairstyle be reduced through balancing the training data?

Kagan Ozturk, Haiyu Wu, Kevin W. Bowyer

Appearance of a face can be greatly altered by growing a beard and mustache. The facial hairstyles in a pair of images can cause marked changes to the impostor distribution and the…

Identity Overlap Between Face Recognition Train/Test Data: Causing Optimistic Bias in Accuracy Measurement

Haiyu Wu, Sicong Tian, Jacob Gutierrez +3

A fundamental tenet of pattern recognition is that overlap between training and testing sets causes an optimistic accuracy estimate. Deep CNNs for face recognition are trained for…