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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探索，探索新的无标记动作捕捉系统（例如 Perception Neuron 和 Posenet）在舞蹈作品的远程创作、排练、教学和表演中的功能。其中包括：经济实惠且易于使用的动作捕捉技术作为编舞的创意工具实时远程信息处理舞蹈交流舞蹈编排的远程协作设计在线和互动表演远程表演排练虚拟空间中的虚拟编舞智能机器编舞（机器学习）舞蹈编排的三维远程教学表演舞蹈动作的抽象生成美学可视化我们将交付：一个用于舞者（和视听创意人员）远程远程练习、排练和表演的运动数据的框架。该框架包括：一个代码模板入门套件，供创意人员设计a）自定义动作可视化和b）虚拟表演的外观和体验一个可供在线观众通过数字设备与表演互动的可控界面一个动作和手势数据库，可用于训练舞者和机器软件之间基于机器学习的交互的动作模型该项目解决了舞蹈公司对可用技术超越视频限制的迫切需求会议平台。随着这些公司从巡演和新作品制作转向其他活动，我们将充分利用时间和资源来研究编舞实践的潜在未来，并在全球范围内以数字方式共享。