InteractML: Making machine learning accessible for creative practitioners working with movement interaction in immersive media

InteractML: Making machine learning accessible for creative practitioners working with movement interaction in immersive media
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InteractML:让在沉浸式媒体中从事运动交互的创意从业者能够使用机器学习

DOI:
10.1145/3489849.3489879
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发表时间:
2021
期刊:
--
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通讯作者:
Hilton C
Hilton C
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--
作者:
Hilton C

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交互式机器学习提供了一种设计运动交互的方法,该方法支持创作者在他们的沉浸式应用程序中实现复杂的运动设计,只需用他们的身体来执行它们。我们引入了一个新的工具,InteractML,和一个伴随的构思方法,使运动交互设计更快,适应性和访问不同的经验和背景的创作者,如艺术家,舞者和独立的游戏开发人员。该工具专为非专家量身定制,因为创建者通过基于节点的图形和VR界面配置和训练机器学习模型,需要最少的编程。我们的目标是使机器学习民主化,用于运动交互,用于开发一系列创造性和沉浸式应用程序。
Interactive Machine Learning offers a method for designing movement interaction that supports creators in implementing even complex movement designs in their immersive applications by simply performing them with their bodies. We introduce a new tool, InteractML, and an accompanying ideation method, which makes movement interaction design faster, adaptable and accessible to creators of varying experience and backgrounds, such as artists, dancers and independent game developers. The tool is specifically tailored to non-experts as creators configure and train machine learning models via a node-based graph and VR interface, requiring minimal programming. We aim to democratise machine learning for movement interaction to be used in the development of a range of creative and immersive applications.
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