Paper Info
Title
Scan Segments Matching For Pairwise 3d Alignment
Abstract
This paper presents a method for pairwise 3D alignment which solves data association by matching scan segments across scans. Generating accurate segment associations allows to run a modified version of the Iterative Closest Point (ICP) algorithm where the search for point-to-point correspondences is constrained to associated segments. The novelty of the proposed approach is in the segment matching process which takes into account the proximity of segments, their shape, and the consistency of their relative locations in each scan. Scan segmentation is here assumed to be given (recent studies provide various alternatives [10], [19]). The method is tested on seven sequences of Velodyne scans acquired in urban environments. Unlike various other standard versions of ICP, which fail to recover correct alignment when the displacement between scans increases, the proposed method is shown to be robust to displacements of several meters. In addition, it is shown to lead to savings in computational times which are potentially critical in real-time applications.
Year
DOI
Venue
2012
10.1109/ICRA.2012.6224788
2012 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA)
Keywords
Field
DocType
upper bound,shape,image segmentation,pipelines,iterative closest point,measurement,sensors,iterative methods,point to point,object modelling
Pairwise comparison,Pattern recognition,Image matching,Upper and lower bounds,Iterative method,Segmentation,Image segmentation,Data association,Artificial intelligence,Mathematics,Iterative closest point
Conference
ISSN
Citations 
PageRank 
1050-4729
16
0.82
References 
Authors
14
8
Name
Order
Citations
PageRank
Bertrand Douillard128620.50
Alastair James Quadros21486.91
Peter Morton31255.57
James Patrick Underwood444239.37
M. De Deuge5160.82
S. Hugosson6160.82
M. Hallstrom7160.82
Tim Bailey8144085.67