Binocular structured light systems provide better measurements of objects since the measurement field of view is twice that of a monocular measurement system. Pinhole imaging theory is used here to develop expressions for the object reconstruction with binocular structured light. Calibration results are given using Zhang＇s calibration method. Errors in the projector and camera calibrations and systematic errors in the binocular system will cause errors in matching the two sets of 3 D point cloud data. To overcome this, the matrix obtained from the calibration that represents the relationship between the two cameras is used as the initial value for the point cloud matching, with an improved iterative closest points （ICP） algorithm used to speed up the matching. The initially transformed point cloud data is then re matched, further reducing the error to compensate for the calibration errors. Tests show that the two sets of 3 D point cloud data can be well correlated and thecalibration values can be corrected with the improved ICP algorithm. The time for point cloud data matching is reduced to 0.3 seconds.
NETL
NSTL
万方数据
维普
