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Low resolution thermal imaging dataset of sign language digits.
Yeduri, Sreenivasa Reddy; Breland, Daniel Skomedal; Skriubakken, Simen Birkeland; Pandey, Om Jee; Cenkeramaddi, Linga Reddy.
  • Yeduri SR; Department of Information and Communication Technology, University of Agder, Norway.
  • Breland DS; Department of Information and Communication Technology, University of Agder, Norway.
  • Skriubakken SB; Department of Information and Communication Technology, University of Agder, Norway.
  • Pandey OJ; Department of Electronics Engineering, IIT BHU Varanasi, Varanasi 221005, India.
  • Cenkeramaddi LR; Department of Information and Communication Technology, University of Agder, Norway.
Data Brief ; 41: 107977, 2022 Apr.
Article en En | MEDLINE | ID: mdl-35242951
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 32 × 32 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.
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Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Año: 2022 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Año: 2022 Tipo del documento: Article