The state of the art for each category and the available datasets are also presented.

Stereo vision and SfS were the most commonly used algorithms with a combined percentage of 51%. These were stereo vision, structure-from-silhouette (SfS), structure-from-motion (SfM), structured light, time-of-flight (ToF), photometric stereo and tomography. The use of the 3D reconstruction algorithms was also determined.

In each category, facial and fingerprint were predominant, and their respective percentages were 80% and 54.55%. The face is further categorized into facial, ear, iris and skull, while the hand is divided into fingerprint, finger vein and palm. The corresponding percentages for these categories were 74.07%, 20.37% and 5.56%, respectively. Three main categories of 3D biometrics were identified. The research was conducted using the Scopus database. The first taxonomy of 3D biometrics is also presented. This work is a comprehensive review of 3D biometrics since 2011 and presents the related work, the hardware used and the datasets available. The main reason for this was the growing need for more features in the images to create more reliable identification models. Biometrics have been used to identify humans since the 19th century.

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