A point cloud registration method based on stereovision movement tracking is proposed in this paper. The movement tracking and analysis system is composed of a stereovision measurement system and target bars. Target bars are fixed on a structured light profile scanning system. Retro-reflect target points pasted on the bars are captured by the stereovision measurement system to compute location and orientation of the scanner. The scanner is controlled to move in the view field of the movement tracking system to complete a whole scan of the large scale object. Transformation parameters including the rotation matrixes and translation vectors between local scanning coordinate systems and the global movement tracking coordinate system are computed by tracking the retro-reflect target points. Then, local cloud data of each scan is transformed into the global tracking coordinate system which is obviously an easier registration method. Experimental system is built and experiments are carried out. A movement tracking experiment is designed to give a maximum error of movement tracking less than 0.3 millimeters. Registration algorithm is verified useful by another experiment which gives a complete profile scanning of a large scale fan blade work piece. Accuracy experiments are designed to result in an average registration error less than 0.3 millimeters and standard deviation less than 0.2 millimeters.© (2010) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.