Modeling and compression of motion capture data

M. Khan, Muhammad Arif, Arshad Kamal
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引用次数: 3

Abstract

Motion capture (MoCap) system uses sensors or markers, placed on human body joints, to record the movements of a human in space over time. Motion capture data is used in many entertainment applications such as in virtual reality environments to drive avatars, in video games to animate characters, in movies to produce CG effects, etc. In this paper, we present an efficient method for modeling and compression of motion capture data. The method uses quadratic Bezier curve fitting to smoothly model and compress the MoCap data. The temporal variation of MoCap data of each joint is approximated and parameterized using Bezier segments. Simulation results shows that our method uses smaller storage and better visual quality compared to other methods. The low degree of quadratic Bezier curve ensures computationally efficiency required for the realtime gaming applications.
运动捕捉数据的建模和压缩
动作捕捉(MoCap)系统使用放置在人体关节上的传感器或标记来记录人类在空间中随时间的运动。动作捕捉数据用于许多娱乐应用,例如在虚拟现实环境中驱动化身,在视频游戏中动画角色,在电影中产生CG效果等。本文提出了一种有效的运动捕捉数据建模和压缩方法。该方法采用二次Bezier曲线拟合对动作捕捉数据进行平滑建模和压缩。每个关节的动作捕捉数据的时间变化采用Bezier分段进行逼近和参数化。仿真结果表明,与其他方法相比,我们的方法占用了更小的存储空间和更好的视觉质量。二次贝塞尔曲线的低阶保证了实时游戏应用所需的计算效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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