Nuzzi Cristina, Pasinetti Simone, Pagani Roberto, Coffetti Gabriele, Sansoni Giovanna
Department of Mechanical and Industrial Engineering (DIMI), University of Brescia, Brescia, Italy.
Data Brief. 2021 Jan 30;35:106791. doi: 10.1016/j.dib.2021.106791. eCollection 2021 Apr.
The HANDS dataset has been created for human-robot interaction research, and it is composed of spatially and temporally aligned RGB and Depth frames. It contains 12 static single-hand gestures performed with both the right-hand and the left-hand, and 3 static two-hands gestures for a total of 29 unique classes. Five actors (two females and three males) have been acquired performing the gestures, each of them adopting a different background and light conditions. For each actor, 150 RGB frames and their corresponding 150 Depth frames per gesture have been collected, for a total of 2400 RGB frames and 2400 Depth frames per actor. Data has been collected using a Kinect v2 camera intrinsically calibrated to spatially align RGB data to Depth data. The temporal alignment has been performed offline using MATLAB, aligning frames with a maximum temporal distance of 66 ms. This dataset has been used in [1] and it is freely available at http://dx.doi.org/10.17632/ndrczc35bt.1.
HANDS数据集是为机器人与人类交互研究而创建的，它由空间和时间对齐的RGB帧和深度帧组成。它包含用右手和左手执行的12种静态单手手势，以及3种静态双手手势，总共29个独特类别。已采集了五名演员（两名女性和三名男性）执行这些手势的情况，他们每个人都采用了不同的背景和光照条件。对于每个演员，每个手势收集了150个RGB帧及其相应的150个深度帧，每个演员总共收集了2400个RGB帧和2400个深度帧。数据是使用经过内部校准的Kinect v2相机收集的，以便将RGB数据与深度数据进行空间对齐。时间对齐是使用MATLAB离线执行的，将帧的最大时间距离对齐为66毫秒。该数据集已在[1]中使用，可在http://dx.doi.org/10.17632/ndrczc35bt.1上免费获取。
