Vehicle Point Cloud Data Enhancement Method Combined with Panoramic Image

In this paper, a method of vehicular point cloud data enhancement with panoramic image is proposed. Firstly, the classification of point cloud data and the extraction of single object interested are realized by combining DBSCAN(density-based spatial clusterig of applications with noise) segmentation algorithm and typical features of objects; then, the missing area is detected and the corresponding edge is extracted one by one for a point cloud of single object; finally, a region growth dense matching based on panoramic image with local affine transform is proposed. The method is used to generate the 3D point data in the missing area, and to enhance the point cloud data. Experiment results show that this method can fill the missing area of cloud data in streetscape, and the result of point cloud enhancement is real and reliable.