The BioHDD Dataset
A Dataset for Studying Biometric Identification on Heavily Degraded Data.
101 Participants
2 Sessions
10 Noise Factors
Visible + NIR
The purpose of this dataset is to deliver biometric data under demanding imaging conditions, allowing to evaluate both existing and new biometric methods based on facial traits. It contains data captured from 101 subjects, simultaneously on the visible and near-infrared spectrum, under four straining factors: illumination angle; head revolution; head tilting and camera exposure.
The imaging framework was installed in a dark lounge, deprived of any exterior light source. Data was captured under 8 different illumination angles and participant revolutions, on 45° steps. For both acquisition phases, volunteers were captured facing forward, tilting their heads up and down, and under three exposure levels. Apart from that, ground truth high-quality frontal and side images were captured for each participant.
Two distinct image acquisition sessions were performed, separated by at least two week interval. Volunteers were picked randomly and are at large majority young Caucasian people, approximately 2/3 men and 1/3 women. Images were manually cropped to a rectangular format (600 x 600 pixel), centered on the head.
Degradation factors introduced in the acquisition stage:
Illum. Angle
Participants' heads were imaged while illuminated from different angles, covering all 360° at 45° steps.
Illum. Intensity
Photos where taken with different illumination intensities, ranging from 5% to 100%.
Revolution
Subject revolution was also introduced over eight angles, in a similar manner to the illumination angle variation.
Head Tilt
Three different levels of head-tilting were registered, with participants facing forward, up and down.
Additional degradation procedures:
Blur
To mimic the issues associated with inappropriate lens settings, poor focus, subject movement, etc., Gaussian filtering was used with σ ranging from 5 to 20.
Occlusion
Face occlusion were simulated overlapping a black patch to the original image, covering 15% to 20% of the picture.
Rev. Occlusion
Reverse Occlusion is different flavor of the occlusion degradation, where only a small portion of the image (20% to 5%) is left visible.
Pixelization
Related with low or insufficient spatial resolution devices, or post-processing censorship, was obtained by downscaling the original photo (100x100px to 25x25px).
Storage/Transmission related degradation:
Compression
The compression degradation that can be found on systems relying on digital storage or broadcasting was simulated using a standard JPEG compression algorithm with low quality settings (20% to 5%).
White Noise
Based on the same reasoning, the issues associated with storage on photographic film or broadcasting through analog channels were simulated adding white noise.