| Abstract | In this paper, we propose a feature-based model to recognize emotions via touching patterns of individuals playing a game on a typical tablet. In this work, novel features, such as Angular Velocity/Acceleration, Angle, Curl, Area and number of strokes within a time window, are introduced and the gold-standard of the data is determined automatically via subjects’ facial expressions. The results show that the approach is promising and the model is able to recognize all the six basic emotions, with a performance of 71.92%±0.51. In addition, the recognition of valence and arousal reaches correlation coefficients equal to 0.76 and 0.78 respectively | |
| Year | 2019 | |
| Keywords | Affective Computing; | |
| Authors | Mojgan Hashemian, Rui Prada, Pedro A Santos, João Dias, Samuel Mascarenhas | |
| Pages | 1--7 | |
| Publisher | IEEE | |
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@article { hashemian19, abstract = {In this paper, we propose a feature-based model to recognize emotions via touching patterns of individuals playing a game on a typical tablet. In this work, novel features, such as Angular Velocity/Acceleration, Angle, Curl, Area and number of strokes within a time window, are introduced and the gold-standard of the data is determined automatically via subjects’ facial expressions. The results show that the approach is promising and the model is able to recognize all the six basic emotions, with a performance of 71.92%±0.51. In addition, the recognition of valence and arousal reaches correlation coefficients equal to 0.76 and 0.78 respectively}, keywords = {Affective Computing;}, pages = {1--7}, publisher = {IEEE}, title = {Inferring Emotions from Touching Patterns}, year = {2019}, author = {Mojgan Hashemian and Rui Prada and Pedro A Santos and João Dias and Samuel Mascarenhas} } |
Inferring Emotions from Touching Patterns
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