Research on UAV 3D Modeling and Measurement Based on Point Cloud Fusion Algorithm
Excessive coordinate residuals are the main reason for the substandard accuracy of UAV 3D modeling.In order to avoid the above situation,the UAV 3D modeling and measurement method based on point cloud fusion algorithm is studied.The cloud correspondence between 2D sample points,3D sample points and target viewpoint is determined.The point cloud fu-sion algorithm model is established by solving the bilinear fusion difference,and then is combined with the definition conditions of UAV target contour points to complete the matching of target Hu distance,then the necessary UAV target nodes can be ob-tained,and the UAV target extraction can be realized based on the point cloud fusion algorithm.A 3D measurement coordinate system is established,3D images are corrected according to the value range of optical distortion,and the calculation formula of the point operator is derived by combining the relevant measurement nodes,so as to determine the value range of the measure-ment adjustment,and complete the design of the 3D modeling and measurement method of the UAV.The experimental results show that under the action of point cloud fusion algorithm,the coordinate residuals of X axis,Y axis and Z axis are less than 10％,which can realize the accurate construction of UAV 3D measurement model.
point cloud fusion algorithm3D modelingtarget Hu distanceoptical distortion differenceimage correction
万方数据
维普
