Paper Info
Title
Super 4PCS Fast Global Pointcloud Registration via Smart Indexing
Abstract
Data acquisition in large-scale scenes regularly involves accumulating information across multiple scans. A common approach is to locally align scan pairs using Iterative Closest Point ICP algorithm or its variants, but requires static scenes and small motion between scan pairs. This prevents accumulating data across multiple scan sessions and/or different acquisition modalities e.g., stereo, depth scans. Alternatively, one can use a global registration algorithm allowing scans to be in arbitrary initial poses. The state-of-the-art global registration algorithm, 4PCS, however has a quadratic time complexity in the number of data points. This vastly limits its applicability to acquisition of large environments. We present Super 4PCS for global pointcloud registration that is optimal, i.e., runs in linear time in the number of data points and is also output sensitive in the complexity of the alignment problem based on the unknown overlap across scan pairs. Technically, we map the algorithm as an 'instance problem' and solve it efficiently using a smart indexing data organization. The algorithm is simple, memory-efficient, and fast. We demonstrate that Super 4PCS results in significant speedup over alternative approaches and allows unstructured efficient acquisition of scenes at scales previously not possible. Complete source code and datasets are available for research use at http://geometry.cs.ucl.ac.uk/projects/2014/super4PCS/.
Year
DOI
Venue
2014
10.1111/cgf.12446
Comput. Graph. Forum
Keywords
Field
DocType
graphics
Source code,Computer science,Search engine indexing,Theoretical computer science,Artificial intelligence,Time complexity,Iterative closest point,Speedup,Data point,Computer vision,Data acquisition,Algorithm,Point cloud
Journal
Volume
Issue
ISSN
33
5
0167-7055
Citations 
PageRank 
References 
87
2.46
29
Authors
3
Name
Order
Citations
PageRank
Nicolas Mellado116812.23
Dror Aiger231515.76
Niloy J. Mitra33813176.15