@inproceedings{504977be29cf4bf68fd37c2cc5234d0a,
title = "6DOF point cloud alignment using geometric algebra-based adaptive filtering",
abstract = "In this paper we show that a Geometric Algebra-based least-mean-squares adaptive filter (GA-LMS) can be used to recover the 6-degree-of-freedom alignment of two point clouds related by a set of point correspondences. We present a series of techniques that endow the GA-LMS with outlier (false correspondence) resilience to outperform standard least squares (LS) methods that are based on Singular Value Decomposition (SVD). We furthermore show how to derive and compute the step size of the GA-LMS.",
author = "Anas Al-Nuaimi and Eckehard Steinbach and Lopes, \{Wilder B.\} and Lopes, \{Cassio G.\}",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; IEEE Winter Conference on Applications of Computer Vision, WACV 2016 ; Conference date: 07-03-2016 Through 10-03-2016",
year = "2016",
month = may,
day = "23",
doi = "10.1109/WACV.2016.7477642",
language = "English",
series = "2016 IEEE Winter Conference on Applications of Computer Vision, WACV 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2016 IEEE Winter Conference on Applications of Computer Vision, WACV 2016",
address = "United States",
}