Patent ID: 8462992
Filing Date: 2013-06-11
Classification: G06K

Abstract:
1. A method of building model change detection, comprising steps of: (a) after data co-registration, detection of ground areas and vegetation areas, and discrete point elimination on ground areas and vegetation areas, calculating height differences between earlier-period three-dimensional (3D) building models and later-period lidar point clouds; and (b) categorizing said points having height differences to decide change types of said 3D building models step by step, wherein said later-period lidar point clouds has later-period ground areas and later-period vegetation areas; and wherein said change types of said 3D building models comprises no change, main-structure change, micro-structure change, change of building demolished, vegetation occluded, and undefined change, (a1) through data co-registration of said earlier-period 3D building models, said later-period lidar point clouds and later-period multi-spectral stereo-aerial images, obtaining 3D coordinates of control points by identifying and measuring building corners of said building models, said lidar point clouds and said aerial images; (a2) obtaining a digital surface model (DSM) of land surface elevation and a digital elevation model (DEM) of ground elevation from said lidar point clouds; subtracting heights in DEM from heights in DSM to obtain a normalized digital surface model (nDSM); and setting a height threshold of ground to identify ground areas; (a3) obtaining normalized difference vegetation indexes (NDVI) from areas having spectrums of red light and infrared light in said aerial images to obtain vegetation areas in unoccluded image areas; and, for occluded image areas, obtaining vegetation areas from a texture image of said nDSM through a maximum likelihood classification while using said detected vegetation areas as training data; (a4) eliminating said lidar point clouds on said ground areas and said vegetation areas; (a5) obtaining triangulated irregular networks (TIN) from said lidar point clouds after eliminating said ground areas and said vegetation areas; obtaining vertical triangles through judging normal vectors of said TIN; and eliminating wall points which are lowest points of said vertical triangles; and (a6) obtaining plane equations of roofs by calculating coordinates of said building corners and obtaining height distances between roofs of said lidar point clouds and roofs of said building models.