UWB-gestures, a public dataset of dynamic hand gestures acquired using impulse radar sensors
Autor: | Sung Ho Cho, Jun-Young Park, Dingyang Wang, Shahzad Ahmed |
---|---|
Jazyk: | angličtina |
Rok vydání: | 2021 |
Předmět: |
Statistics and Probability
Data Descriptor Scientific community Computer science Science 02 engineering and technology Impulse radar Library and Information Sciences 01 natural sciences Field (computer science) Pattern Recognition Automated law.invention Education Deep Learning law Research community 0202 electrical engineering electronic engineering information engineering Humans Computer vision Detection theory Radar Gestures business.industry Deep learning 010401 analytical chemistry Hand Electrical and electronic engineering 0104 chemical sciences Computer Science Applications Gesture recognition 020201 artificial intelligence & image processing Artificial intelligence Statistics Probability and Uncertainty business Gesture Information Systems |
Zdroj: | Scientific Data, Vol 8, Iss 1, Pp 1-9 (2021) Scientific Data |
ISSN: | 2052-4463 |
DOI: | 10.1038/s41597-021-00876-0 |
Popis: | In the past few decades, deep learning algorithms have become more prevalent for signal detection and classification. To design machine learning algorithms, however, an adequate dataset is required. Motivated by the existence of several open-source camera-based hand gesture datasets, this descriptor presents UWB-Gestures, the first public dataset of twelve dynamic hand gestures acquired with ultra-wideband (UWB) impulse radars. The dataset contains a total of 9,600 samples gathered from eight different human volunteers. UWB-Gestures eliminates the need to employ UWB radar hardware to train and test the algorithm. Additionally, the dataset can provide a competitive environment for the research community to compare the accuracy of different hand gesture recognition (HGR) algorithms, enabling the provision of reproducible research results in the field of HGR through UWB radars. Three radars were placed at three different locations to acquire the data, and the respective data were saved independently for flexibility. Measurement(s) hand gesture • voluntary movement behavior Technology Type(s) ultra-wideband impulse radar • Imaging Technology Factor Type(s) type of hand gesture • participant Sample Characteristic - Organism Homo sapiens Sample Characteristic - Environment human house Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.13181240 |
Databáze: | OpenAIRE |
Externí odkaz: |