Biometrics: Going 3D

Abstract

Biometrics have been used to identify humans since the 19th century. Over time, these biometrics became 3D. The main reason for this was the growing need for more features in the images to create more reliable identification models. This work is a comprehensive review of 3D biometrics since 2011 and presents the related work, the hardware used and the datasets available. The first taxonomy of 3D biometrics is also presented. The research was conducted using the Scopus database. Three main categories of 3D biometrics were identified. These were face, hand and gait. The corresponding percentages for these categories were 74.07%, 20.37% and 5.56%, respectively. The face is further categorized into facial, ear, iris and skull, while the hand is divided into fingerprint, finger vein and palm. In each category, facial and fingerprint were predominant, and their respective percentages were 80% and 54.55%. The use of the 3D reconstruction algorithms was also determined. These were stereo vision, structure-from-silhouette (SfS), structure-from-motion (SfM), structured light, time-of-flight (ToF), photometric stereo and tomography. Stereo vision and SfS were the most commonly used algorithms with a combined percentage of 51%. The state of the art for each category and the available datasets are also presented. Finally, multimodal biometrics, generalization of 3D reconstruction algorithms and anti-spoofing metrics are the three areas that should attract scientific interest for further research. In addition, the development of devices with 2D/3D capabilities and more publicly available datasets are suggested for further research.

Brave New Healthcare: A Narrative Review of Digital Healthcare in American Medicine

“…Biometric identification typically uses facial features, fingerprints, the iris, veins in the finger, or gait for identification, but other forms of physical identification are possible [87]. Novel systems requiring three different biometric identifications for added security are being developed and have achieved over 99% accuracy [88].…”

“…Novel systems requiring three different biometric identifications for added security are being developed and have achieved over 99% accuracy [88]. Security issues and data privacy have given rise of the transition from two-dimensional biometric systems to 3D biometrics [87]. New research is exploring the use of electroencephalogram (EEG) signals for biometrics [89].…”