Real-time 3D point cloud registration

Three-dimensional (3D) registration or matching is a crucial step in 3D model reconstruction. In this work, we develop a real-time 3D point cloud registration technology. Firstly, in order to achieve real-time 3D data acquisition, the stereo phase unwrapping method is utilized to eliminate the ambiguity of the wrapped phase, assisted with the depth constraint strategy without projecting any additional patterns or embedding any auxiliary signals. Then we implement SLAM-based coarse registration and ICP-based fine registration to match the point cloud data after the rapid identification of two-dimensional (2D) feature points. In order to improve the efficiency of 3D registration, the relative motion of the measured object at each coarse registration is quantified, through which only one fine registration is performed after several coarse registrations. The experiment shows that, the complex model can be registered in real time to reconstruct its whole 3D model with our method.