运动捕捉
计算机视觉
阿凡达
计算机科学
人工智能
运动(物理)
双眼视觉
立体视觉
人体运动
匹配(统计)
人机交互
数学
统计
作者
Bo Sheng,Linfeng Chen,Cheng Jian,Yanxin Zhang,Zikai Hua,Jing Tao
出处
期刊:Measurement
[Elsevier]
日期:2024-02-01
卷期号:225: 113908-113908
被引量:1
标识
DOI:10.1016/j.measurement.2023.113908
摘要
This study aimed to achieve precise 3D human motion data acquisition without the need for markers. Specifically, the proposed system utilized two affordable cameras to capture human motion from diverse angles. It developed a lightweight Open Pose algorithm to extract 2D human body joints from recorded videos. Subsequently, a stereo-matching method was applied to derive accurate 3D human body joint data. Comprehensive experiments with 10 healthy participants showcased the system's exceptional performance, demonstrating superior measurement accuracy compared to established standards like the NOKOV system (RMSE values consistently below 9°) and commonly used Microsoft Kinect devices (V2 and Azure). This innovative binocular vision system presents a new approach to motion capture, potentially offering a cost-effective and precise tool for practical applications across various scenarios (e.g., motor functional assessment, virtual avatar streaming), contributing significantly to both scientific and academic communities.
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