We introduce two methods for the registration of range images when a prior estimate of the transformation between views is not available and the overlap between images is relatively small. The methods are an extension to the work of Gueziec and Ayache (1994) and Turk and Levoy (1994) and consists of 2 stages. First, we find the initial estimated transformation by extracting and matching 3D space curves from different scans of the same object. If no salient features are available on the object we use fiducial marks to find the initial transformation. This allows us to always find a satisfactory and even highly accurate transformation independent of the geometry of the object. Second, we apply a modified iterative closest points algorithm (ICP) to improve the accuracy of registration. We define a weighted distance function based on surface curvature which can reduce the number of iterations and requires a less accurate initial estimate of the transformation.
Recommended citation: Allen, Peter K. and Ruigang Yang, Registering, Integrating, and Building CAD Models from Range Data, IEEE Int. Conf. on Robotics and Automation, May 18-20, 1998, Leuven, Belgium, pp. 3115-3120.