Method to automatically register scattered point clouds based on principal pose estimation

Feng Li; David Stoddart; Carl Hitchens

doi:10.1117/1.OE.56.4.044107

26 April 2017 Method to automatically register scattered point clouds based on principal pose estimation

Feng Li, David Stoddart, Carl Hitchens

Author Affiliations +

Optical Engineering, Vol. 56, Issue 4, 044107 (April 2017). https://doi.org/10.1117/1.OE.56.4.044107

Abstract

Three dimensional (3-D) modeling is important in applications ranging from manufacturing to entertainment. Multiview registration is one of the crucial steps in 3-D model construction. The automatic establishment of correspondences between overlapping views, without any known initial information, is the main challenge in point clouds registration. An automatic registration algorithm is proposed to solve the registration problem of rigid, unordered, scattered point clouds. This approach is especially suitable for registering datasets that are lacking in features or texture. In general, the existing techniques exhibit significant limitations in the registration of these types of point cloud data. The presented method automatically determines the best coarse registration results by exploiting the statistical technique principal component analysis and outputs translation matrices as the initial estimation for fine registration. Then, the translation matrices obtained from coarse registration algorithms are used to update the original point cloud and the optimal translation matrices are solved using an iterative algorithm. Experimental results show that the proposed algorithm is time efficient and accurate, even if the point clouds are partially overlapped and containing large missing regions.

Citation Download Citation

Feng Li, David Stoddart, and Carl Hitchens "Method to automatically register scattered point clouds based on principal pose estimation," Optical Engineering 56(4), 044107 (26 April 2017). https://doi.org/10.1117/1.OE.56.4.044107

Received: 17 February 2017; Accepted: 10 April 2017; Published: 26 April 2017

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