Updating thermal imaging dataset of hand gestures with unique labels

Sreenivasa Reddy Yeduri; Daniel Skomedal Breland; Om Jee Pandey; Linga Reddy Cenkeramaddi

doi:10.1016/j.dib.2022.108037

Updating thermal imaging dataset of hand gestures with unique labels

Data Brief. 2022 Mar 8:42:108037. doi: 10.1016/j.dib.2022.108037. eCollection 2022 Jun.

Authors

Sreenivasa Reddy Yeduri¹, Daniel Skomedal Breland¹, Om Jee Pandey², Linga Reddy Cenkeramaddi¹

Affiliations

¹ ACPS Group, Department of Information and Communication Technology, University of Agder, Norway.
² Department of Electronics Engineering, IIT(BHU), Uttar Pradesh 221005, India.

Abstract

An update to the previously published low resolution thermal imaging dataset is presented in this paper. The new dataset contains high resolution thermal images corresponding to various hand gestures captured using the FLIR Lepton 3.5 thermal camera and Purethermal 2 breakout board. The resolution of the camera is $160 \times 120$ with calibrated array of 19,200 pixels. The images captured by the thermal camera are light-independent. The dataset consists of 14,400 images with equal share from color and gray scale. The dataset consists of 10 different hand gestures. Each gesture has a total of 24 images from a single person with a total of 30 persons for the whole dataset. The dataset also contains the images captured under different orientations of the hand under different lighting conditions.

Keywords: Hand Gestures; Machine learning models; Sensor; Thermal Camera; Thermal imaging.