NDLI: Quality assessment for LiDAR point cloud registration using in-situ conjugate features

Content Provider	IEEE Xplore Digital Library
Author	Jen-Yu Han Hui-Ping Tserng Chih-Ting Lin
Copyright Year	2011
Description	Author affiliation: Graduate Institute of Electronics Engineering, National Taiwan University, Taipei, Taiwan (Chih-Ting Lin) \|\| Department of Civil Engineering, National Taiwan University, Taipei, Taiwan (Jen-Yu Han; Hui-Ping Tserng)
Abstract	This study aims to develop a quantitative approach for evaluating the quality of a LiDAR point cloud registration solution. First, a highly-efficient technique for integrating multiple LiDAR point clouds was introduced using directly the in-situ conjugate features (including point, linear, planar features and groups of points). Then by applying the Non-Iterative Solutions for Linear Transformations (NISLT) technique, the transformation between datasets can be directly solved without carrying out iterative computations or using any prior initial information. The weighted model for the observables was also developed to improve the reliability of obtained solutions. Finally, two quality indexes, namely the absolute consistency and relative geometric similarity, were proposed to give complete and realistic information on the quality of the integrated solutions. A case study for a real-field facility has also been performed to reveal the distinguishing capability and superiority of this newly-developed technique.
Starting Page	4122
Ending Page	4125
File Size	312446
Page Count	4
File Format	PDF
ISBN	9781457710032
ISSN	21537003
e-ISBN	9781457710056
DOI	10.1109/IGARSS.2011.6050140
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-07-24
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Laser radar Indexes Vectors Feature extraction Remote sensing Bridges Transmission line matrix methods quality assessment Light Detection and Ranging point registration parameter estimation
Content Type	Text
Resource Type	Article

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