基于多约束融合的人手臂三维运动分析

为了在没有任何特殊标志的情况下,实现从单目序列图象中分析、估计人手臂的三维运动,提出了一种多约束融合的方法,该方法是利用棍棒模型来模拟人的手臂,首先通过处理单目图象序列来自动获取图象序列中手臂关节点的对应;然后再利用多约束融合及基于图象序列中关节点的对应,即估计尺度意义下关节点的三维相对运动轨迹;最后利用真实图象来获得相应人手臂的三维运动轨迹,并将其与通过运动捕捉系统获得的人手臂的真实三维运动轨迹进行了比较实验。实验结果表明,该方法用于对人手臂的运动分析非常有效。

3D Motion Analysis of Human Arm Based on Multi-Constraints Fusion

Motion estimation of human from a single or a monocular sequence of image is an important research field in Computer Vision and Image Processing. In this paper, based on constraint fusion, we proposed 3D motion estimation from the monocular perspective images without any special markers. We consider the arm as stick model with three joints, and the link between every two neighboring joint points is regarded as rigidity. Based on the knowledge of anatomy and kinematics, we exert coplanar constraint, rigidity constraint, smooth motion constraint on this model. By pre processing the image sequence, we semi automatically yielded 2D correspondences of joint points of arm among images. Then, by constraint fusion, 3D relative structure of arm can be determined in a scale factor. The experiment with real images is included. In order to testify the validity of the proposed method, we compare the 3D motion of human arm obtained by the motion capture system with that obtained by our method. The result shows that the method is very efficient.