The application of motion-capture technology in telematic and virtual dance performance through a framework for long-distance remote communication

通过远程通信框架将动作捕捉技术应用于远程信息处理和虚拟舞蹈表演

基本信息

批准号：
AH/V009826/1
负责人：
Daniel Strutt
金额：
$ 8.9万
依托单位：
Goldsmiths University of London
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2020
资助国家：
英国
起止时间：
2020 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=AH%2FV009826%2F1
关键词：
application motion capture technology telematic

项目摘要

This project involves a unique use-case and experimental exploration of the affordances of new marker-less motion-capture systems such as Perception Neuron and Posenet in the remote creation, rehearsal, teaching, and performance of dance work. Aspects of this are:Affordable and accessible motion-capture technology as a creative tool for choreographyReal-time telematic dance communicationRemote collaborative devising of dance choreographyOnline and interactive performanceRemote rehearsal of performanceVirtual choreography in virtual spacesChoreography with intelligent machines (machine learning)Remote teaching of dance choreography in three dimensionsAbstracted generative aesthetic visualisation of dance movement for performanceWe will deliver:A framework for long-distance remote communication of movement data for dancers (and audio-visual creatives) to practice, rehearse and perform remotely but together. This framework includes:A code template starter-kit for creatives to design a) custom movement visualizations and b) appearances and experiences for virtual performanceA controllable interface for online audiences to interact with performances through a digital deviceA database of movements and gestures that can be used to train movement models for machine-learning-based interactions between dancers and machine softwareThis project addresses an urgent need for useable technology for dance companies to move beyond the limitations of video conferencing platforms. As these companies pivot from touring and the production of new work to other activities, we will make a strong case for the application of time and resources into streams of research into potential futures of choreographic practice that can be digitally shared worldwide.

该项目涉及独特的用例和实验性探索，对新的无标记运动捕捉系统（例如感知神经元和波西纳特）在远程创作，彩排，教学和舞蹈工作表现中提供的负担。其各个方面是：可负担且易于访问的动作捕获技术，是一种创造性的工具，用于编舞舞蹈连通舞会的舞蹈编排，舞蹈编舞online和互动性表演表演式练习表演的互动式练习式练习练习式虚拟舞会编排，以智能机器（机器学习）远程教学的虚拟空间编排中在三维的消除舞蹈中，舞蹈运动的舞蹈运动可视化表演：我们将提供：一个框架，用于远距离远程远距离对舞者（和视听创意者）进行运动数据的远距离通信，以练习，彩排和远程表演，但可以一起练习。该框架包括：用于设计创意的代码模板启动器套件a）自定义运动可视化和b）虚拟性能可控接口的外观和体验，用于在线受众，通过数字devicea的动作数据库和可以使用的手势与性能进行交互培训运动模型，以基于机器学习的舞者与机器软化项目之间的基于机器学习的互动，该项目迫切需要舞蹈公司超越视频会议平台的局限性。当这些公司从巡回演出和新作品的生产到其他活动的过程中，我们将有很大的理由将时间和资源应用于可以在全球范围内以数字方式共享的编舞实践的潜在未来的研究流。