Updating thermal imaging dataset of hand gestures with unique labels
- PMID:35341036
- PMCID: PMC8943409
- DOI: 10.1016/j.dib.2022.108037
Updating thermal imaging dataset of hand gestures with unique labels
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 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.
© 2022 The Author(s).
Conflict of interest statement
The authors declare that there is no influence from known competing financial interests or personal relationships which have, or could be perceived for the work reported in this article.
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