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Found 5 papers, 1 papers with code
Artificial Pupil Dilation for Data Augmentation in Iris Semantic Segmentation
The results indicate that our data augmentation method can improve segmentation accuracy up to 15% for images with high pupil dilation, which creates a more reliable iris recognition pipeline, even under extreme dilation.
Learning to Predict Fitness for Duty using Near Infrared Periocular Iris Images
This research proposes a new database and method to detect the reduction of alertness conditions due to alcohol, drug consumption and sleepiness deprivation from Near-Infra-Red (NIR) periocular eye images.
Towards an Efficient Semantic Segmentation Method of ID Cards for Verification Systems
The best results for the fused multi-country dataset of ID Card images from Chile, Argentina and Mexico reached an IoU of 0. 9911.
Semantic Segmentation of Periocular Near-Infra-Red Eye Images Under Alcohol Effects
The purpose of the system is to measure the fitness for duty.
Selfie Periocular Verification using an Efficient Super-Resolution Approach
Selfie-based biometrics has great potential for a wide range of applications since, e. g. periocular verification is contactless and is safe to use in pandemics such as COVID-19, when a major portion of a face is covered by a facial mask.
