A novel two-stage algorithm for accurate registration of 3-D point clouds

Accurate registration of 3-D point clouds is a common problem in computer vision. This paper presents a new two-stage algorithm for point clouds registration. A novel local invariant feature which is a k-dimensional vector is proposed and used in our coarse registration stage. Two new structural con...

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Bibliographic Details
Published in2011 International Conference on Multimedia Technology pp. 6187 - 6191
Main Authors Jiajing Dai, Jie Yang
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2011
Subjects
3-D point cloud
Algorithm design and analysis
Computer vision
Estimation
ICP algorithm
Iterative closest point algorithm
local invariant feature
Mathematical model
Robustness
two-stage registration
Visualization
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ISBN1612847714
9781612847719
DOI10.1109/ICMT.2011.6001978

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Summary:Accurate registration of 3-D point clouds is a common problem in computer vision. This paper presents a new two-stage algorithm for point clouds registration. A novel local invariant feature which is a k-dimensional vector is proposed and used in our coarse registration stage. Two new structural constraints combined with the Iterative Closest Point (ICP) algorithm are adopted in our fine registration stage. The accuracy and effectiveness of our algorithm is visually and quantitatively demonstrated by the comparative experiments on synthetic and real 3-D data.
ISBN:1612847714
9781612847719
DOI:10.1109/ICMT.2011.6001978