面向立体视觉结构光三维重建系统的点云误差补偿方法

Point cloud error compensation method for stereo structured light 3D reconstruction system

  • 摘要: 为了提高立体视觉结构光三维重建系统的精度,提出了一种面向立体视觉结构光三维重建系统的点云误差补偿方法,该方法分为误差标定、误差建模和误差补偿三部分。首先,提出一种新的误差标定方法,将立体视觉结构光系统的测量空间划分为离散的特征点并标定了整个空间内特征点的误差;然后,提出了基于神经网络的误差建模方法,建立起该空间的误差模型;最后,提出了适用于立体视觉结构光系统的点云误差补偿方法,将建立的误差模型用于误差补偿。实验表明文章提出的误差补偿方法平均减少了51.96%的直径误差和14.16%的球心距误差,精度提升效果明显。从而,验证了该算法的有效性和可行性。

     

    Abstract: In order to improve the accuracy of stereo structured light 3D reconstruction system, a point cloud error compensation method is proposed. The method is divided into three parts: error calibration, error modeling and error compensation. Firstly, a new error calibration method is proposed, which divides the measurement space of stereo vision structured light system into discrete feature points, and calibrates the error of feature points in the whole space. Secondly, the error modeling method based on neural network is proposed, and the error model of this space is established. Finally, a point cloud error compensation method suitable for stereo vision structured light system is proposed. After experiments, it is proved that the proposed error compensation method reduces the diameter error by 51.96% and the sphere center distance error by 14.16%, respectively. The effectiveness and feasibility of this algorithm are also verified.

     

/

返回文章
返回