A modified iterative closest point algorithm for shape registration

Dmitrii Tihonkih; Artyom Makovetskii; Vladislav Kuznetsov

doi:10.1117/12.2237911

28 September 2016 A modified iterative closest point algorithm for shape registration

Dmitrii Tihonkih, Artyom Makovetskii, Vladislav Kuznetsov

Proceedings Volume 9971, Applications of Digital Image Processing XXXIX; 99712D (2016) https://doi.org/10.1117/12.2237911
Event: SPIE Optical Engineering + Applications, 2016, San Diego, California, United States

Abstract

The iterative closest point (ICP) algorithm is one of the most popular approaches to shape registration. The algorithm starts with two point clouds and an initial guess for a relative rigid-body transformation between them. Then it iteratively refines the transformation by generating pairs of corresponding points in the clouds and by minimizing a chosen error metric. In this work, we focus on accuracy of the ICP algorithm. An important stage of the ICP algorithm is the searching of nearest neighbors. We propose to utilize for this purpose geometrically similar groups of points. Groups of points of the first cloud, that have no similar groups in the second cloud, are not considered in further error minimization. To minimize errors, the class of affine transformations is used. The transformations are not rigid in contrast to the classical approach. This approach allows us to get a precise solution for transformations such as rotation, translation vector and scaling. With the help of computer simulation, the proposed method is compared with common nearest neighbor search algorithms for shape registration.

Citation Download Citation

Dmitrii Tihonkih, Artyom Makovetskii, and Vladislav Kuznetsov "A modified iterative closest point algorithm for shape registration", Proc. SPIE 9971, Applications of Digital Image Processing XXXIX, 99712D (28 September 2016); https://doi.org/10.1117/12.2237911

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available