摘要：

为快速精准定位脑电图的源信号,设计一套新的摄影测量系统。该系统通过CCD相机与TOF相机结合来定位源信号,将深度相机获取的三维点云数据替代深度图像进行标定,从而提高相机标定精度。利用三维扫描仪获取实际数据,将重建出的脑部电极的结果数据与实际数据进行比较。实验结果表明,该系统测量平均距离误差为3.26 mm,与改进前的方法(平均距离误差6.13 mm)相比,精度有较大提高。

关键词: 摄影测量, 脑电图, 相机标定, 飞行时间法, 点云

Abstract: To locate the source signal,a photogrammetric system is designed,which combines the CCD camera with the Time of Flight (TOF)camera.To calibrate the camera group accurately,a method is introduced in this paper which uses the point cloud image directly rather than depth image.Experimental results indicate that the average distance error of reconstruction in this study is 3.26 mm,which is better than traditional calibration method (6.13 mm). Aiming at the problem of slow speed and poor accuracy of model segmentation and feature surface recognition,a point cloud segmentation and surface recognition method based on connected component labeling and probabilistic method is proposed.A zero-value fixed curvature normalization method is proposed by estimating the curvature of the point cloud and the curvature of the point cloud.Based on the initial clustering of curvature on the point cloud,the connected region marker method is used to segment the point cloud,and then the statistical method is used to judge the feature type surface of the point cloud.Experimental results show that the proposed method can meet the demand for processing small and medium size point clouds in the segmentation and application of feature surface of mechanical parts based on regular surfaces.

Key words: photogrammetry, Electroencephalogram(EEG), camera calibration, Time of Flight(TOF), point cloud

中图分类号: 

• TP63