In recent years, the interest of numerous fields for gestural interaction and gesture recognition has risen. While some of them can afford the use of various devices like gloves and armbands, artists favor more discreet techniques to maximize the impact of the integration of gestural interaction on their audience. The goal of this master thesis was to study and assess the potential of such interactions for interactive artistic systems, only using computer vision. By means of an Intel RealSense D435 camera and the Cubemos Skeleton TrackingSDK, different movement features to sound features mappings have been tested in order to identify the most intuitive and guessable ones for the users. This work presents the followed approach and the results it provided.
| Date of Award | 25 Jun 2020 |
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| Original language | French |
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| Awarding Institution | |
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| Supervisor | Bruno Dumas (Supervisor) |
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Gestural Interaction for an Artistic SoundControl System
Trinon, C. (Author). 25 Jun 2020
Student thesis: Master types › Master in Computer Science Professional focus in Software engineering