MoveBox:为Microsoft Rocketbox Avatar Library民主化动作捕捉

Mar González-Franco, Zelia Egan, Matt Peachey, Angus Antley, Tanmay Randhavane, Payod Panda, Yaying Zhang, Cheng Yao Wang, Derek F. Reilly, Tabitha C. Peck, A. S. Won, A. Steed, E. Ofek
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引用次数: 22

摘要

本文介绍了MoveBox一个开源的工具箱,用于将动画动作捕捉(MoCap)移动到Microsoft Rocketbox的化身库中。动作捕捉使用单个深度传感器执行,如Azure Kinect或Windows Kinect V2。动作捕捉使用单个深度传感器(如Azure Kinect或Windows Kinect V2)实时执行,或者利用深度学习计算机视觉技术从现有的RGB视频中离线提取。我们的工具箱通过转换具有不同关节和层次的系统之间的转换来实现用户化身的实时动画。工具箱的其他功能包括录音,播放和循环动画,以及基本的音频口型同步,闪烁和调整头像的大小以及手指和手动画。我们的主要贡献是创建这个开源工具,以及在不同设备上的验证和最终用户对MoveBox功能的讨论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
MoveBox: Democratizing MoCap for the Microsoft Rocketbox Avatar Library
This paper presents MoveBox an open sourced toolbox for animating motion captured (MoCap) movements onto the Microsoft Rocketbox library of avatars. Motion capture is performed using a single depth sensor, such as Azure Kinect or Windows Kinect V2. Motion capture is performed in real-time using a single depth sensor, such as Azure Kinect or Windows Kinect V2, or extracted from existing RGB videos offline leveraging deep-learning computer vision techniques. Our toolbox enables real-time animation of the user’s avatar by converting the transformations between systems that have different joints and hierarchies. Additional features of the toolbox include recording, playback and looping animations, as well as basic audio lip sync, blinking and resizing of avatars as well as finger and hand animations. Our main contribution is both in the creation of this open source tool as well as the validation on different devices and discussion of MoveBox’s capabilities by end users.
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