Three-dimensional Reconstruction Of The Building Integrated Airborne And Vehicle Borne LiDAR Data

Three dimensional building models is the important part of digital city construction. It has wide application in the field of civil navigation and urban management. How to quickly set up the fine model contains the detail characteristics is one of the key problems in the current solution of 3D modeling technology. This paper establishes the 3D refined model reconstruction technique process integrated utilization airborne and vehicle-borne LiDAR point data, based on the summary and analysis of the existing 3D reconstruction technology. The experimental area of the paper is in Tongbai road Central Plains District of Zhengzhou city. Based on the registration of airborne and vehicle-borne LiDAR point cloud data, the relevant technology to launch the research on building roof characteristics and fa?ade details of feature extraction and model reconstruction, the main content of this paper includes the following four parts.1. The registration of airborne and vehicle-borne LiDAR point cloud. Firstly,using the field measurement control points to position the outline position of the airborne and vehicle-borne point cloud data.Respectively,in the two kind of data control points in the vicinity of the corresponding position to select a range of point could data to carry on the plan fitting, by fitting characteristics of plan more calculating translation parameter and rotation parameter of registration and realizes the airborne and vehicle-borne accurate registration of point cloud data.2. The extracting of roof feature based on airborne LiDAR data. Firstly, this paper adopts gradual triangulation filtering algorithm, through calculating the laser point cloud data candidate to TIN interpolation surface distance as a condition to determine whether a point belonging to the ground, to isolate the ground points and non-ground points; Then in the non-ground points by using the TIN filtering method in neighboring height difference and auxiliary plane extract building point cloud; the use of adjacent normal vector similarity clustering and region growing algorithm on data of roof surface segmentation; further by detection of building Alpha Shape edge point extraction method of contour line, and rule processing of contour vector map building.3. The extraction of building facade. Firstly, based on the Vehicle-borne LIDAR Data, extracting building contour line by using point cloud height and Projection point density of point cloud. In order to make full use of the details of building facade reflected by the Vehicle-borne LIDAR Data, the paper uses the method of the extended projection point density, gets four corner coordinates of buildings’ windows and builds the window model by extracting the contour points of the window,establishing Grid then doing classification and clustering processing.4. Combined with the streetscape and the buildings characteristics of the experimental area to fuse the extraction of building top surface and bottom contour vector images, and improve the detail features of the building to achieve a precise modeling of the experimental area of the building.