The purpose of the airborne LiDAR system calibration is to eliminate the influence of system error and improve the precision of the original point cloud data. In certain hypothesis of flight conditions, the directly positioning model for LiDAR can be reduced to a quasi-rigorous model, and the dependence on the original observation data for the system calibration model is reduced too. In view of the shortcoming of human interaction way to establish corresponding relationship between strips, an improved ICP method which considering the object features in point clouds is proposed to get the transform relationship between strips, and the automatic calibration procedures of LiDAR system is established in this paper. Taking with the real LiDAR data in Baotou test field, experiment results show that the proposed system calibration procedures can greatly eliminate the influence of system error.
KEYWORDS: 3D modeling, LIDAR, Data modeling, Reconstruction algorithms, Remote sensing, Data acquisition, Image segmentation, Detection and tracking algorithms, Corner detection, Data fusion
Since manual surface reconstruction is very costly and time consuming, the development of automatic algorithm is of
great importance. In this paper a fully automated technique based on hierarchical structure analysis of the building to
extract urban building models from LIDAR data is presented. In the processing of reconstruction, the existing automatic
algorithm can solve some simple building reconstructions, such as flat roof, gabled roof. As to complex buildings, many
researchers use external information or manual interaction for help because of the complexity of the reconstruction and
the uncertainty of the building models especially in urban areas. The contour has the characteristics of closed loop, not
intersect and deterministic topological relationship, which can be used to extract building ROI (region of interesting). A
contours tree is constructed, the topological relationships between the different contours which extracted by TIN from
the LIDAR data are established, then the relationships among each hierarchical model can be determined by the analysis
of the topological relationship among contour clusters and a component tree corresponding to the building can be
constructed by tracing the contours tree. The accurate edges of hierarchical model can be gained by the "polarized
cornerity index"-based polygonal approximation of the contour. Especially, a 3D model recognition based on 2D shape
recognition is employed. According to the characteristics of the contours, the category of the primitive parts can be
classified. We assemble the hierarchical models by using the topological relationships among layers, then, the complete
model of the building can be obtained. Experimental results show that the proposed algorithm is suitable for
automatically producing building models including most complex buildings from LIDAR data in urban areas.
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