The MareXperience exhibition event was held in Procida on February 22 and 23, 2019, inside an ancient cave for the shelter of fishermen’s boats, 45 meters long and 8 meters wide. Inside, synchronized video projections and soundscapes were produced to create an immersive virtual environment, whose contents were inspired by the signs and fluidity of underwater life. The digital forms were generated by a Swarm Intelligence algorithm, a tool generally used to create complex kinematic structures defined by a large number of parameters. Generative design is an expressive form aimed at artistic languages and representation of dynamic contexts, which here have been integrated into a narrative process, connecting aspects of the recording of the movement of bodies in water with the principles of data visualization.

MareXperience. AI/AR for the recognition and enhancement of reality / Repola, Leopoldo; Maioli, Andra; Martignoni, Matteo; Scotto di Carlo, Nicola. - (2021). [org/10.3280/oa-686.51]

MareXperience. AI/AR for the recognition and enhancement of reality

Leopoldo Repola
Primo
;
2021

Abstract

The MareXperience exhibition event was held in Procida on February 22 and 23, 2019, inside an ancient cave for the shelter of fishermen’s boats, 45 meters long and 8 meters wide. Inside, synchronized video projections and soundscapes were produced to create an immersive virtual environment, whose contents were inspired by the signs and fluidity of underwater life. The digital forms were generated by a Swarm Intelligence algorithm, a tool generally used to create complex kinematic structures defined by a large number of parameters. Generative design is an expressive form aimed at artistic languages and representation of dynamic contexts, which here have been integrated into a narrative process, connecting aspects of the recording of the movement of bodies in water with the principles of data visualization.
2021
9788835116875
MareXperience. AI/AR for the recognition and enhancement of reality / Repola, Leopoldo; Maioli, Andra; Martignoni, Matteo; Scotto di Carlo, Nicola. - (2021). [org/10.3280/oa-686.51]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/886005
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