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Published on: July 10, 2019
Low resolution thermal imaging dataset of sign language digits
Sreenivasa Reddy Yeduri1, Daniel Skomedal Breland1, Simen Birkeland Skriubakken1
1Department of Information and Communication Technology, University of Agder, Norway.
Abstract:
The dataset contains low resolution thermal images corresponding to various sign language digits represented by hand and captured using the Omron D6T thermal camera. The resolution of the camera is pixels. Because of the low resolution of the images captured by this camera, machine learning models for detecting and classifying sign language digits face additional challenges. Furthermore, the sensor's position and quality have a significant impact on the quality of the captured images. In addition, it is affected by external factors such as the temperature of the surface in comparison to the temperature of the hand. The dataset consists of 3200 images corresponding to ten sign digits, 0-9. Thus, each sign language digit consists of 320 images collected from different persons. The hand is oriented in various ways to capture all of the variations in the dataset.

