Share Email Print
cover

Proceedings Paper

Robust 3D reconstruction using LiDAR and N - visual image
Author(s): Prakash Duraisamy; Stephen Jackson; Kamesh Namuduri; Mohammed S. Alam; Bill Buckles
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

3D image reconstruction is desirable in many applications such as city planning, cartography and many vision applications. The accuracy of the 3D reconstruction plays a vital role in many real world applications. We introduce a method which uses one LiDAR image and N conventional visual images to reduce the error and to build a robust registration for 3D reconstruction. In this method we used lines as features in both the LiDAR and visual images. Our proposed system consists of two steps. In the first step, we extract lines from the LiDAR and visual images using Hough transform. In the second step, we estimate the camera matrices using a search algorithm combined with the fundamental matrices for the visual cameras. We demonstrate our method on a synthetic model which is an idealized representation of an urban environment.

Paper Details

Date Published: 29 April 2013
PDF: 9 pages
Proc. SPIE 8748, Optical Pattern Recognition XXIV, 874808 (29 April 2013); doi: 10.1117/12.2016357
Show Author Affiliations
Prakash Duraisamy, Massachusetts Institute of Technology (United States)
Stephen Jackson, Univ. of North Texas (United States)
Kamesh Namuduri, Univ. of North Texas (United States)
Mohammed S. Alam, Univ. of South Alabama (United States)
Bill Buckles, Univ. of North Texas (United States)


Published in SPIE Proceedings Vol. 8748:
Optical Pattern Recognition XXIV
David Casasent; Tien-Hsin Chao, Editor(s)

© SPIE. Terms of Use
Back to Top