H2020Индивидуална стипендия2020–2022

E2-CREATE · Encoding Embodied CreativityVisual arts, performing arts, film, design

„Хоризонт 2020“ — Действия „Мария Склодовска-Кюри“

Период: 2020-04-06 → 2022-09-13
Финансиране от ЕС: 212 934 €
Участници: 1
Схема: MSCA-IF

Линиите свързват координатора с партньорите.

Накратко на български

Връзката между танца и компютърното изкуство се изследва чрез създаване на софтуер и модели за машинно обучение, които дигитализират човешките движения. Това помага за по-доброто разбиране на тялото като източник на творчество и развива нови технологии в дигиталното изкуство.

Този кратък обзор е генериран от изкуствен интелект

Кратко обяснение, генерирано от езиков модел по текста на CORDIS. Оригиналът е по-долу.

Резултати накратко

E2-CREATE: Encoding Embodied CreativityVisual arts, performing arts, film, design

Issue being Addressed Dance represents a rich resource of bodily expertise that is exciting and challenging for other scientific and artistic domains to draw from. E2-Create addresses this challenge by providing generative approaches to facilitate the exchange between dance and computer-based art. E2-Create places a strong focus on the combination of software development and artistic creation informed by recent progress in dance digitisation, machine learning (ML), and generative art. Importance for Society While dance plays an important role in society, its role as an artistic form of investigation that relies on embodied creativity remains under-appreciated. Furthermore, dance as a complex artform that is difficult to record constitutes a challenging, but rich domain for digital technology. Because of this, dance can contribute to future developments in digital technology, which in turn impacts society at large. E2-Create highlights how tightly dance, as embodied creativity, and digital technology practices can be intertwined to achieve a high level mutual exchange between the two for research, development, and creation. This has the potential to increase public awareness for embodied forms of knowledge and its importance for research and development of digital technology. Overall Objectives E2-Create has four main objectives: Gain an understanding of principles of embodied creativity. Evaluate existing ML models and computer simulations for their suitability in dance. Develop new ML models and computer simulations for dance creation. Disseminate project results among artists, scientists, students and the general public.

Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз

Цел на проекта

Choreography is an art form well-known for combining rigorous physical and mental training with the highest degrees of creativity. However, as dance is the most ephemeral of art forms, this extraordinary embodied creativity has been in danger of disappearing without leaving a significant trace. That was until several leading dance artists began over a decade ago to experiment with digital technology as a means to document their unique approaches to choreography. The result today is an impressive accumulation of interdisciplinary research showing how embodied creativity in dance can be systematically studied and documented, how computer-aided design can effectively communicate the outcomes and how digitised recordings can be processed computationally to reveal new information about choreographic principles, processes and methods. Drawing on these developments in dance digitisation and recent progress in computational arts, the Fellowship will focus on fusing artistic skills in dance with artistic skills in computing. The goal is to achieve a new level of sophisticated creative transfer at the intersection of the two fields by taking advantage of significant advances in the fields of computer vision and machine learning combined with the high-level of expertise the Fellow brings from the field of generative computer art. Generative computer art techniques have until now not been integrated fully into the dance digitisation process, but they have extraordinary potential in combination with machine learning to expand the capability of computational systems to learn from and model existing artistic approaches. The Fellow’s extensive experience of working at the intersection between dance technology and computer art and science means he is extremely well placed to facilitate and achieve this encoding of embodied creativity with lasting impact for mixed machine-human collaboration and interdisciplinary art and science research.

Оригинален текст от CORDIS (на английски).

Участници

COVENTRY UNIVERSITY · CoventryКоординаторОбединеното кралство