Matlab 源码在三维点数据中拟合长方体.zip

# Cuboid-Fitting-RanSAC #### RanSAC based cuboid fitting. [](https://www.mathworks.com/matlabcentral/fileexchange/65168-cuboid-fit-ransac) ## Run: Use runme.m to execute the example. The script fits the cuboid on 3D points and displays cuboid model, inliers, and outliers. Two 3D point-clouds are included: /3D Point Data/Box.mat /3D Point Data/Box_other.mat In runme.m these point-clouds are used as examples. In runme.m Load your 3D data in this format: points3D = [X, Y, Z] where, X - x-coordiantes of point data, column vector Y - y-coordiantes of point data, column vector Z - z-coordiantes of point data, column vector ## CuboidRANSAC: ``` [model, CuboidParameters, inlierIndices, outlierIndices] = CuboidRANSAC( points3D ) ``` CuboidRANSAC - Computes the best fitting cuboid on the 3D points using RANSAC. If *90* percent points are in the consensus set or *1000* iterations are reached, the code terminates and the current best is returned. Inputs: points3D - nx3 Matric containing the 3D points placed in rows. points3D = [X, Y, Z] Outputs: model - 8x3 Matric containing the corners of the best-fit cuboid CuboidParameters - 9x1 Matric containing the parameters of the best-fit. Namely, centre, scale and orientation. [centre_x centre_y centre_z length width height roll pitch yaw] inlierIndicies - Linear indices of inlier points within the input point cloud, returned as a column vector. outlierIndices - Linear indices of outlier points within the input point cloud, returned as a column vector.