DocumentCode
1798823
Title
Mean shift clustering segmentation and RANSAC simplification of color point cloud
Author
Zhang Ximin ; Wan Wanggen ; Xiao Li ; Ma Junxing
Author_Institution
Sch. of Commun. & Inf. Eng., Shanghai Univ., Shanghai, China
fYear
2014
fDate
7-9 July 2014
Firstpage
837
Lastpage
841
Abstract
This paper extends mean shift algorithm to 3D color point cloud, and successfully realizes its clustering segmentation. Then with these segmentation blocks, we use Random Sample Consensus (RANSAC) algorithm to calculate each block´s approximate plane, and keep the points which are the nearest to the plane, thus the point cloud is simplified. The experiment shows that our simplifying results are perfect.
Keywords
image colour analysis; image segmentation; iterative methods; pattern clustering; probability; 3D color point cloud; RANSAC simplification; mean shift clustering segmentation algorithm; probability density estimator; random sample consensus algorithm; Clustering algorithms; Density functional theory; Equations; Fitting; Kernel; Mathematical model; Three-dimensional displays; RANSAC simplification; color point cloud; mean shift;
fLanguage
English
Publisher
ieee
Conference_Titel
Audio, Language and Image Processing (ICALIP), 2014 International Conference on
Conference_Location
Shanghai
Print_ISBN
978-1-4799-3902-2
Type
conf
DOI
10.1109/ICALIP.2014.7009912
Filename
7009912
Link To Document