Omkar2118/datasets huggingface dataset:
Tecnocampus Hand Image Database

The acquisition over the VIS and TIR data was performed by a commercial thermal camera Testo 882-3. We have used a second external camera to obtain the NIR data. In this case we have built a NIR camera using a webcam changing the default optical filter for a couple of Kodak filters for IR. We have also used a printed circuit board with 16 infra-red LEDs that provide the infra-red illumination.

In order to alleviate the variability on the way the users present their hand we have used a kind of removable mask/template. Users had to put their hand in a neoprene surface with the help of a hand mask. Once the hand is placed the mask was removed and the three images (VIS, NIR, TIR) were shot. The same process was repeated with the palmar hand side, but using the mask in the opposite position (flip up to down).

Once the first acquisition was finished (no more than a minute) the user performed some exercise in order to change hand heat conditions. This step was carried out in less than 30 seconds so that when finished, the user proceeded again with the second acquisition. For each session a total of 12 hand images were captured per user.

Introducing paper: Thermal hand image segmentation for biometric recognition
CARL Database

Visible and thermal images have been acquired using a thermographic camera TESTO 880-3, equipped with an uncooled detector with a spectral sensitivity range from 8 to 14 μm and provided with a germanium optical lens, and an approximate cost of 8.000 EUR. For the NIR a customized Logitech Quickcam messenger E2500 has been used, provided with a Silicon based CMOS image sensor with a sensibility to the overall visible spectrum and the half part of the NIR (until 1.000 nm approximately) with a cost of approx. 30 EUR. We have replaced the default optical filter of this camera by a couple of Kodak daylight filters for IR interspersed between optical and sensor. They both have similar spectrum responses and are coded as wratten filter 87 and 87C, respectively. In addition, we have used a special purpose printed circuit board (PCB) with a set of 16 infrared leds (IRED) with a range of emission from 820 to 1.000 nm in order to provide the required illumination.

The thermographic camera provides a resolution of 160×120 pixels for thermal images and 640×480 for visible images, while the webcam provides a still picture maximum resolution of 640×480 for near-infrared images and this has been the final resolution selected for our experiments.

A couple of halogen focus disposed 30 degrees away from the frontal direction and about 3 m away from the user, match the artificial light of the room. Note that all the tripods and structures have fixed markings on the ground.

Introducing paper: A new face database simultaneously acquired in visible, near infrared and thermal spectrum
EasyCall corpus

EasyCall corpus is a dysarthric speech command dataset in Italian. The dataset consists of 21386 audio recordings from 24 healthy and 31 dysarthric speakers, whose individual degree of speech impairment was assessed by neurologists through the Therapy Outcome Measure.

Introducing paper: EasyCall corpus: a dysarthric speech dataset