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A Fast Point Cloud Segmentation Algorithm Based on Region Growth

EasyChair Preprint no. 1048

2 pagesDate: May 28, 2019

Abstract

Point cloud segmentation is a key prerequisite for object classification recognition. We propose a fast region growing algorithm by using the neighborhood search, filter sampling, Euclidean clustering and region growth. Segmentation experiment on point cloud data in indoor environment demonstrated that segmentation accuracy and efficiency were improved by the proposed algorithm.

Keyphrases: Euclidean clustering, point cloud segmentation, regional growth

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@Booklet{EasyChair:1048,
  author = {Xiaofeng Ma and Wei Luo and Mingquan Chen and Jiahui Li and Xin Yan and Xia Zhang and Wei Wei},
  title = {A Fast Point Cloud Segmentation Algorithm Based on Region Growth},
  howpublished = {EasyChair Preprint no. 1048},

  year = {EasyChair, 2019}}
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