CRC for Spatial Information

The team developed new algorithms for 3D building reconstruction from lidar point clouds. The Extended Gaussian Image method was adopted to improve classification of lidar points and generation of surface patches, which allow for efficient reconstruction of buildings including buildings roofs as well as building walls.

Based on extensive literature review, the Project team designed multi-source, multi-sensor data fusion/registration models and algorithms. In particular, the team explored mutual information approach since it can accommodate different data sources. An implementation of this approach has been done with Matlab that shows good potential to integrate multi-source remote sensing data for spatial data management in general and for automated feature extraction in particular.

They have further developed building detection from aerial imagery and lidar data, especially separation of buildings and trees; and investigated extraction of geometric primitives for object reconstruction.

2 PhD students, Yuxiang He and Ebaadat Parmehr, are progressing well in their project research.