3D reconstruction of buildings from LiDAR data considering various types of roof structures

In this article, a different approach has been proposed to detect and reconstruct buildings in 3D space. In this regard, some potentially primary features were produced and a genetic algorithm (GA) was employed in order to select the optimum features. The selected features were utilized to detect the building by using k-nearest neighbour (k-NN) algorithm. The detection results were used as inputs of reconstruction procedure. The proposed approach for 3D reconstruction consists of three main steps: roof planes were separated in the first step. Then, the corners of each plane boundary were extracted in order to provide the roof reconstruction possibility. Finally, the walls were reconstructed and merged to roofs and the final 3D model was obtained. Results evaluation indicated that the average value of buildings detection in the test areas was 87.84% in Quality. Moreover, the average value of buildings reconstruction in the test areas was 76.95% in object based Quality, and 95.66% in Quality of building planes that were greater than 25 m2, respectively. Also, the average of altimetric and planimetric RMS of the test areas were 0.3 m and 0.75 m, respectively.