Depth camera based dataset of hand gestures

Autor: Sindhusha Jeeru, Arun Kumar Sivapuram, David González León, Jade Gröli, Sreenivasa Reddy Yeduri, Linga Reddy Cenkeramaddi
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Data in Brief, Vol 45, Iss , Pp 108659- (2022)
Druh dokumentu: article
ISSN: 2352-3409
DOI: 10.1016/j.dib.2022.108659
Popis: The dataset contains RGB and depth version video frames of various hand movements captured with the Intel RealSense Depth Camera D435. The camera has two channels for collecting both RGB and depth frames at the same time. A large dataset is created for accurate classification of hand gestures under complex backgrounds. The dataset is made up of 29718 frames from RGB and depth versions corresponding to various hand gestures from different people collected at different time instances with complex backgrounds. Hand movements corresponding to scroll-right, scroll-left, scroll-up, scroll-down, zoom-in, and zoom-out are included in the data. Each sequence has data of 40 frames, and there is a total of 662 sequences corresponding to each gesture in the dataset. To capture all the variations in the dataset, the hand is oriented in various ways while capturing.
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