Affiliations: Key Laboratory of Information and Computing Science, Guizhou Normal University, Guiyang, Guizhou 550003, China | E-mail: songliu@gznu.edu.cn
Correspondence:
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Corresponding author: Key Laboratory of Information and Computing Science, Guizhou Normal University, Guiyang, Guizhou 550003, China. E-mail: songliu@gznu.edu.cn.
Abstract: In order to detect the deformation of ancient buildings completely, accurately and continuously, a time-varying point cloud group is established by using three-dimensional laser scanner to detect and sample ancient buildings in different time periods. By comparing and calculating time-varying point clouds, the deformation of ancient buildings can be comprehensively analysed. In order to improve the efficiency of data processing, a BSP parallel algorithm for deformation analysis based on time-varying point clouds is designed, and the processing and calculation of deformation data are completed by a computing cluster composed of several independent computing units. This method of deformation detection based on time-varying point cloud has been applied to many ancient building detection and protection projects such as Hailongdun site in Zunyi, Guizhou Province China, Huangze Temple in Guangyuan, Sichuan Province China, etc. The application results show that the deformation monitoring method based on time-varying point cloud is quicker, more economical, more accurate and less harmful to ancient buildings than the traditional method. Compared with the general point cloud deformation analysis methods, the accuracy and comprehensiveness of the deformation monitoring results are higher. It can be used as one of the best methods for deformation monitoring of ancient buildings.
Keywords: Ancient building, deformation, detection, point cloud, parallel computing
