19 papers
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 licenses and/or booking photos. The algorithm's rank…
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
The paper proposes using rank‑1 identity consensus across multiple face matchers (1‑consistency) to decide whether a probe is enrolled in a gallery, showing it matches or exceeds t…
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…
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…
Goldilocks Test Sets for Face Verification
Haiyu Wu, Sicong Tian, Aman Bhatta +6
Reported face verification accuracy has reached a plateau on current well-known test sets. As a result, some difficult test sets have been assembled by reducing the image quality o…
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…