论文标题
通过多种kinect v2的非线性三材料开发自校准的运动捕获系统
Development of a Self-Calibrated Motion Capture System by Nonlinear Trilateration of Multiple Kinects v2
论文作者
论文摘要
在本文中，开发了基于Kinect的分布式和实时运动捕获系统。采用三角法来计算使用校准棒的Kinect V2传感器的相对位置，并自动注册传感器的位置。通过将多个传感器的结果与非线性最小平方法相结合，可以优化运动捕获的精度。此外，为了排除传感器不准确的结果，在遮挡方法中应用了计算几何形状，该方法发现了遮挡的关节数据。同步方法基于NTP协议，该协议可以动态地同步服务器和客户端的时钟之间的时间，从而确保所提出的系统是实时系统。从校准，遮挡，准确性和效率的角度进行验证验证系统的实验。此外，为了证明我们系统的实际性能，对先前开发的运动捕获系统（线性三材料方法和几何三材料方法）进行了比较，其中进行了基准测试光学系统，其中表明我们提出的系统的准确性是38.3 \％$ $ $ $ 38.3 \％$和24.1％，而不是两位属性系统，分别是更好的。
In this paper, a Kinect-based distributed and real-time motion capture system is developed. A trigonometric method is applied to calculate the relative position of Kinect v2 sensors with a calibration wand and register the sensors' positions automatically. By combining results from multiple sensors with a nonlinear least square method, the accuracy of the motion capture is optimized. Moreover, to exclude inaccurate results from sensors, a computational geometry is applied in the occlusion approach, which discovers occluded joint data. The synchronization approach is based on an NTP protocol that synchronizes the time between the clocks of a server and clients dynamically, ensuring that the proposed system is a real-time system. Experiments for validating the proposed system are conducted from the perspective of calibration, occlusion, accuracy, and efficiency. Furthermore, to demonstrate the practical performance of our system, a comparison of previously developed motion capture systems (the linear trilateration approach and the geometric trilateration approach) with the benchmark OptiTrack system is conducted, therein showing that the accuracy of our proposed system is $38.3\%$ and 24.1% better than the two aforementioned trilateration systems, respectively.
