EAGER: Efficient control and transmission of digital puppetry

EAGER:数字木偶的高效控制和传输

基本信息

项目摘要

Digital puppetry refers to the interactive control of virtual characters. This approach can be useful in any virtual experience where a synthetic character?s interactivity must surpass the current capabilities of AI. Examples of this include teacher training; projecting remote docents into museums, science centers and networked virtual environments; and preparing soldiers for their first tours of duty in foreign lands. The objective of this project is to improve the quality and breadth of experiences that can be provided by the puppeteering paradigm, especially when the puppeteer is working from a remote location such as his or her home and the experience is taking place in a location with limited network connectivity. The intent is to reduce latency and bandwidth requirements; cost and complexity of experience creation, capture and delivery; and cognitive load on puppeteers ? while still providing support for complex behaviors. This exploratory research project focuses on micro-poses that can be recognized and assembled into more complex actions. The PI seeks to rapidly identify these poses via the fusion of multiple inexpensive sources of sensor data and the physical constraints appropriate for our virtual characters. The PI approaches the tension between precision and network demand by using these micro-poses to reduce cost, footprint of the puppetry motion capture, and networking demands, while simultaneously increasing the effectiveness and accessibility of the puppeteering paradigm. The focus on accessibility leads to the development of techniques that can be run at interactive rates on in-home tabletop systems, facilitating connections between mentors and mentees across the globe.
数字木偶戏是指对虚拟角色的交互控制。这种方法可以在任何虚拟体验中使用,其中合成字符?人工智能的交互性必须超越目前人工智能的能力。这方面的例子包括教师培训;将远程讲解员投射到博物馆、科学中心和网络虚拟环境中;以及为士兵在外国土地上的第一次图尔斯服役做准备。该项目的目标是提高木偶表演范式所能提供的体验的质量和广度,特别是当木偶表演者在他或她的家中等远程位置工作时,以及体验发生在网络连接有限的位置时。其目的是减少延迟和带宽需求;体验创建、捕获和交付的成本和复杂性;以及木偶师的认知负荷?同时仍然为复杂的行为提供支持。这个探索性研究项目的重点是可以识别并组装成更复杂的动作的微姿势。PI试图通过融合多个廉价的传感器数据源和适合我们虚拟角色的物理约束来快速识别这些姿势。PI通过使用这些微姿态来降低成本,木偶动作捕捉的足迹和网络需求,同时提高木偶操纵范例的有效性和可访问性,从而接近精度和网络需求之间的紧张关系。对可访问性的关注导致了技术的发展,这些技术可以在家庭桌面系统上以互动的速度运行,促进了地球仪上导师和学员之间的联系。

项目成果

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Charles Hughes其他文献

Using AI-Based Virtual Companions to Assist Adolescents with Autism in Recognizing and Addressing Cyberbullying
使用基于人工智能的虚拟伴侣帮助自闭症青少年识别和解决网络欺凌问题
  • DOI:
    10.3390/s24123875
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Robinson Ferrer;Kamran Ali;Charles Hughes
  • 通讯作者:
    Charles Hughes

Charles Hughes的其他文献

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{{ truncateString('Charles Hughes', 18)}}的其他基金

EAGER: SaTC-EDU: Improving Cybersecurity Education for Adolescents with Autism Through Automated Augmented Self-Monitoring Applications
EAGER:SaTC-EDU:通过自动增强自我监控应用程序改善自闭症青少年的网络安全教育
  • 批准号:
    2114808
  • 财政年份:
    2021
  • 资助金额:
    $ 19.98万
  • 项目类别:
    Standard Grant
SHB: Small: Collaborative Research: Reducing Alcohol Use Among College Students Using Virtual Role Playing
SHB:小型:合作研究:利用虚拟角色扮演减少大学生饮酒
  • 批准号:
    1116615
  • 财政年份:
    2011
  • 资助金额:
    $ 19.98万
  • 项目类别:
    Standard Grant
Systematic Debuggng of Computer Programs
计算机程序的系统调试
  • 批准号:
    7703308
  • 财政年份:
    1977
  • 资助金额:
    $ 19.98万
  • 项目类别:
    Standard Grant
Restructuring the Undergraduate Learning Environment
重构本科学习环境
  • 批准号:
    7614494
  • 财政年份:
    1976
  • 资助金额:
    $ 19.98万
  • 项目类别:
    Standard Grant

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