Title
Robust 3D Features for Matching between Distorted Range Scans Captured by Moving Systems
Abstract
Laser range sensors are often demanded to mount on a moving platform for achieving the good efficiency of 3D reconstruction. However, such moving systems often suffer from the difficulty of matching the distorted range scans. In this paper, we propose novel 3D features which can be robustly extracted and matched even for the distorted 3D surface captured by a moving system. Our feature extraction employs Morse theory to construct Morse functions which capture the critical points approximately invariant to the 3D surface distortion. Then for each critical point, we extract support regions with the maximally stable region defined by extremal region or disconnectivity. Our feature description is designed as two steps: 1) we normalize the detected local regions to canonical shapes for robust matching, 2) we encode each key point with multiple vectors at different Morse function values. In experiments, we demonstrate that the proposed 3D features achieve substantially better performance for distorted surface matching than the state-of-the-art methods.
Year
DOI
Venue
2014
10.1109/CVPR.2014.378
CVPR
Keywords
Field
DocType
laser range sensor,image capture,image matching,3d feature,robust 3d feature matching,morse function,morse theory,distorted,3d feature extraction,distorted range scan matching,distortion,image reconstruction,image sensors,3d feature, range scan, distorted, moving system,feature extraction,3d reconstruction,3d distorted surface capture,local region detection,feature description,object detection,moving system,support region extraction,invariant critical point capture,range scan
Computer vision,Normalization (statistics),Pattern recognition,Computer science,Critical point (thermodynamics),Feature extraction,Artificial intelligence,Invariant (mathematics),Critical point (mathematics),Distortion,Morse theory,3D reconstruction
Conference
ISSN
Citations 
PageRank 
1063-6919
2
0.36
References 
Authors
16
4
Name
Order
Citations
PageRank
Xiangqi Huang130.71
Bo Zheng215913.62
Takeshi Masuda3765.92
Katsushi Ikeuchi44651881.49