VRBiom

Description

The VRBiom (Virtual Reality Dataset for Biometric Applications) dataset has been acquired using a head-mounted display (HMD) to benchmark and develop various biometric use-cases such as iris and periocular recognition and associated sub-tasks such as detection and semantic segmentation. The VRBiom dataset consists of 900 short videos acquired from 25 individuals recorded in the NIR spectrum. To encompass real-world variations, the dataset includes recordings under three gaze conditions: steady, moving, and partially closed eyes. Additionally, it has maintained an equal split of recordings without and with glasses to facilitate the analysis of eyewear. These videos, characterized by non-frontal views of the eye and relatively low spatial resolutions (400 × 400). The dataset also includes 1104 presentation attacks constructed from 92 PA instruments. These PAIs fall into six categories constructed through combinations of print attacks (real and synthetic identities), fake 3D eyeballs, plastic eyes, and various types of masks and mannequins.

Reference

If you use this dataset, please cite the following publication(s) depending on the use:

@article{vrbiom_dataset_arxiv2024,
author = {Kotwal, Ketan and Ulucan, Ibrahim and \”{O}zbulak, G\”{o}khan and Selliah, Janani and Marcel, S\'{e}bastien},
title = {VRBiom: A New Periocular Dataset for Biometric Applications of HMD},
year = {2024},
month = {Jul},
journal = {arXiv preprint arXiv:2407.02150},
DOI = {https://doi.org/10.48550/arXiv.2407.02150}
}

@inproceedings{vrbiom_pad_ijcb2024,
author = {Kotwal, Ketan and \”{O}zbulak, G\”{o}khan and Marcel, S\'{e}bastien},
title = {Assessing the Reliability of Biometric Authentication on Virtual Reality Devices},
booktitle = {Proceedings of IEEE International Joint Conference on Biometrics (IJCB2024)},
month = {Sep},
year = {2024}      
}