GestureMidAirD3

This dataset is part of the UCR Archive maintained by University of Southampton researchers. Please cite a relevant or the latest full archive release if you use the datasets. See http://www.timeseriesclassification.com/. Data contain 3D hand trajectories collected with Leap Motion device. There are 13 subjects, each performs 26 interface-command gestures. Each gesture is encoded as a sequence of 3D points, representing the position of the dominant-hand forefinger. There are 26 classes corresponding to unique gestures. See Fig. 1 of [2] for the list of gestures and their visualisation. - Class 1: arc3Dleft- Class 2: arc3Dright- Class 3: caret- Class 4: check- Class 5: circle- Class 6: curly-bracket-left- Class 7: curly-bracket-right- Class 8: delete- Class 9: left-swipe- Class 10: pigtail- Class 11: poly3Dxyz- Class 12: poly3Dxzy- Class 13: poly3Dyxz- Class 14: poly3Dyzx- Class 15: poly3Dzxy- Class 16: poly3Dzyx- Class 17: rectangle- Class 18: right-swipe- Class 19: spiral- Class 20: square-bracket-left- Class 21: square-bracket-right- Class 22: star- Class 23: triangle- Class 24: v- Class 25: x- Class 26: zig-zag We make three datasets out of these data, one for each dimension. We follow the original paper (see [2]) and use data of 8 subjects for training and 5 subjects for testing. Data of a same subjects does not appear in both train and test set, so resampling may introduce bias. Data created by Fabio M. Caputo et al. (see [1], [2]). Data edited by Hoang Anh Dau. [1] Github repo: https://github.com/giach68/gesturesCodes[2] Caputo, Fabio M., et al. Comparing 3D trajectories for simple mid-air gesture recognition. Computers & Graphics. 73 (2018): 17-25. Donator: H. A. Dau