利用Kinect的人体动作视觉感知算法

A Visual Perception Algorithm for Human Motion by a Kinect

  • 摘要: 提出了一种面向类人机器人的人体动作视觉感知算法,提高了利用Kinect作为视觉输入设备捕捉到的人体动作数据的精度.首先,通过逆运动学方程将捕捉到的关节位移信息转换成角度信息.然后,以角速度和角加速度的变化为依据,将长时间的运动自动分割成独立片段,并用相关向量机原理估计出高精度的角度轨迹.最后,用角度轨迹的空间相似性、时间相似性、平滑度等指标对该算法进行了评估,并在NAO机器人平台上对算法处理后的动作进行了实验验证.实验结果表明,该算法有效提高了动作感知的时空相似性和轨迹平滑度,为高精度的动作模仿奠定了基础.

     

    Abstract: A visual perception algorithm of human motion for humanoid robot is proposed to improve the precision of the motion data captured from a Kinect. Firstly, the positions of the joints are transformed into the angles according to the inverse kinematics equations. Secondly, the long-time motion is segmented into episodes automatically based on the change of the angular velocity and acceleration, and then RVM (relevant vector machine) is utilized for estimating the angle trajectories with high accuracy. Finally, the spatial consistence, temporal consistence and smoothness of the angle trajectories are given to evaluate the algorithm, and a motion data series processed by the algorithm is implemented on a NAO robot platform. The experimental results indicate that the proposed algorithm effectively improves the spatial and temporal consistence of the motion perception and the smoothness of the trajectory, which provides a foundation for high-precision motion imitation.

     

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