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ABSTRACT:Airborne LiDAR data and optical imagery are two datasets used for 3D building reconstruction. In this paper, the complementarities of these two datasets are utilized to perform a primitive-based 3D building reconstruction. The proposed method comprises following steps: (1) recognize primitives from LiDAR point cloud and roughly measure primitives' parameters as initial values, and (2) select primitives' features on the imagery, and (3) optimize primitives' parameters by the constraints of LiDAR point cloud and imagery, and (4) represent 3D building model by these optimized primitives. Compared with other modelbased or CSG-based methods, the proposed method is simpler. It only uses the most straightforward features, i.e. planes of LiDAR point cloud and points of optical imagery. The experimental result shows this primitive-based method can accurately reconstruct 3D building model. And it can tightly integrate LiDAR point cloud and optical imagery, that is to say, all primitives' parameters are optimized with all constraints in one step.

ABSTRACT:Image has rich color information, and it can help to promote recognition and classification of point cloud. The registration is an important step in the application of image and point cloud. In order to give the rich texture and color information for LiDAR point cloud, the paper researched a fast registration method of point cloud and sequence images based on the ground-based LiDAR system. First, calculating transformation matrix of one of sequence images based on 2D image and LiDAR point cloud; second, using the relationships of position and attitude information among multi-angle sequence images to calculate all transformation matrixes in the horizontal direction; last, completing the registration of point cloud and sequence images based on the collinear condition of image point, projective center and LiDAR point. The experimental results show that the method is simple and fast, and the stitching error between adjacent images is litter; meanwhile, the overall registration accuracy is high, and the method can be used in engineering application.

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