A fast automatic method for registration of partially-overlapping range images
- 27 November 2002
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
Abstract
A popular approach for 3D registration of partially-overlapping range images is the ICP (iterative closest point) method and many of its variations. The major drawback of this type of iterative approaches is that they require a good initial estimate to guarantee that the correct solution can always be found. In this paper, we propose a new method, the RANSAC-basedDARCES (data-aligned rigidity-constrained exhaustive search) method, which can solve the partially-overlapping 3D registration problem efficiently and reliably without any initial estimation. Another important characteristic of our method is that it requires no local features in the 3D data set. An extra characteristic is that, for the noiseless case, the basic algorithm ofour DARCES method can guarantee that the solution it finds is the true one, due to its exhaustive-search nature. Even with the nature of exhaustive search, its time complexity can be shown to be relatively low. Experiments have demonstrated that our method is efficient and reliable for registering partially-overlapping range images.Keywords
This publication has 7 references indexed in Scilit:
- Object modeling by registration of multiple range imagesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- 3D free-form surface registration and object recognitionInternational Journal of Computer Vision, 1996
- Registering multiview range data to create 3D computer objectsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1995
- Structural indexing: efficient 3-D object recognitionPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1992
- A method for registration of 3-D shapesIEEE Transactions on Pattern Analysis and Machine Intelligence, 1992
- Affine invariant model-based object recognitionIEEE Transactions on Robotics and Automation, 1990
- Random sample consensusCommunications of the ACM, 1981