Itekube-7 is a touch gesture dataset of interaction gestures defined for a sequential classification task. Unlike symbolic gestures, whose features are solely spatial, interaction gestures require both spatial and temporal analysis to define them properly. The seven classes of the dataset were chosen for their versatility and in specific cases strong correlations.
This dataset was created with variability in mind at every step:
- The protocol given to perform gestures was minimal, in order to grasp every possible way of performing the said gesture and obtain multiple borderline cases. We could observe variability in speed, positioning, used fingers, timing or amplitude in trajectories.
- Scale and orientation were free.
- Participants were chosen from different area of work, with age ranging from 12 to 62.
- 7 classes
- 27 users
- 6591 gestures
- XML format
- Additional information in the README
Note: In the original paper, the gestures from users 2, 3, 9, 12, 17, 23 and 27 were used to produce the test set.