Point cloud registration for indoor mapping using time-of-flight camera

Disaster monitoring requires for a safety and rapidity. 3D measurement, such as photogrammetry and laser scanning, can satisfy these requirements in a structure inspection and modeling. Aerial photogrammetry and laser scanning are applied to 3D data acquisition in damaged outdoor environments. Recently, the ground-based disaster monitoring also requires 3D data acquisition in indoor environment. We propose a point cloud data alignment methodology based on Iterative Closest Point (ICP) algorithm and SLAM approaches. However, conventional ICP and SLAM use only geometrical features. In other words, we are difficult to align simple planes. Thus, image matching using intensity values taken from TOF camera are integrated into a feature matching for a stable 3D data alignment.