@inproceedings{afaceff1a2e14c079b0c19d14e9032dd,
title = "The registration problem revisited: Optimal solutions from points, lines and planes",
abstract = "In this paper we propose a practical and efficient method for finding the globally optimal solution to the problem of pose estimation of a known object. We present a framework that allows us to use both point-to-point, point-to-line and point-to-plane correspondences in the optimization algorithm. Traditional methods such as the iterative closest point algorithm may get trapped in local minima due to the non-convexity of the problem, however, our approach guarantees global optimality. The approach is based on ideas from global optimization theory, in particular, convex under-estimators in combination with branch and bound. We provide a provably optimal algorithm and demonstrate good performance on both synthetic and real data.",
keywords = "Under-estimators, Non-convexity, Point-to-line, Point-to-plane",
author = "Carl Olsson and Fredrik Kahl and Magnus Oskarsson",
year = "2006",
doi = "10.1109/CVPR.2006.307",
language = "English",
volume = "1",
publisher = "IEEE - Institute of Electrical and Electronics Engineers Inc.",
pages = "1206--1213",
booktitle = "Proceedings - 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2006",
address = "United States",
note = "2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2006 ; Conference date: 17-06-2006 Through 22-06-2006",
}