A Method for Registration of 3-D Shapes

Authors

Paul J. Besl, Neil D. McKay

Year

1992

Journal Paper

Algorithm

ICP

Source

IEEE Transactions on Pattern Analysis and Machine Intelligence

Identifiers

DOI 10.1109/34.121791

Abstract¶

This paper describes a general-purpose, representation-independent method for the accurate and computationally efficient registration of 3-D shapes including free-form curves and surfaces. The method handles the full six degrees of freedom and is based on the iterative closest point (ICP) algorithm, which requires only a procedure to find the closest point on a geometric entity to a given point. The ICP algorithm always converges monotonically to the nearest local minimum of a mean-square distance metric, and the rate of convergence is rapid during the first few iterations. Therefore, given an adequate set of initial rotations and translations for a particular class of objects with a certain level of "shape complexity," one can globally minimize the mean-square distance metric over all six degrees of freedom by testing each initial registration. One important application of this method is to register sensed data from unfixtured rigid objects with an ideal geometric model, prior to shape inspection. Experimental results show the capabilities of the registration algorithm on point sets, curves, and surfaces.

Summary¶

Formalizes the classical Iterative Closest Point algorithm as a representation-independent procedure for rigid 3D shape registration. The paper matters because it gave ICP its canonical point-correspondence/minimum-distance iteration, convergence framing, and broad applicability across point sets, curves, and surfaces.