Strategies for Point clouds and the automation of data fusion of Thermal and Muti-spectral imagery, - based building geometry model generation on COLMAP
Existing cities represent the greatest opportunity to improve building energy efficiency. Cities energy analysis is becoming increasingly important because the data visualisation can results and can assist in the decision makers to make decisions on improving the cities energy efficiency and reducing environmental impacts. The primary objective ofthis research is to automatically collect and reconstruct and merge data imagery into geometry data que can visualize as thermal data of the cities envelope and create a PointCloud geometry model that enved more of one set of data. In the proposed or imagery recollection, a rapid and low-cost data collection hardware system was designed by integrating Thermal and an Multi-spectral cameras. Secondly, several algorithms were created to automatically recognize images envelope as objects from collected raw data. The extracted 3D geometric model was then automatically saved as an industry standard file format for data interoperability. The contributions of this research include 1) a customized low-cost hybrid data collection system development to fuse various data into a thermal point cloud; 2) an automatic method of extracting cities envelope components and its geometry data to generate PointClouds. The broader impacts of this research are that it could offer a new way to collect as is cities data without impeding occupants’ daily life, and provide an easier way for laypeople to understand the energy and vegetation performance of de cities by 3D thermal and NDVI point cloud visualization.