Hierarchical techniques to improve hybrid point cloud registration

Ferran Roure, Xavier Lladó, Joaquim Salvi, Tomislav Privanić, Yago Diez

研究成果: Conference contribution

2 被引用数 (Scopus)

抄録

Reconstructing 3D objects by gathering information from multiple spatial viewpoints is a fundamental problem in a variety of applications ranging from heritage reconstruction to industrial image processing. A central issue is known as the "point set registration or matching" problem. where the two sets being considered are to be rigidly aligned. This is a complex problem with a huge search space that suffers from high computational costs or requires expensive and bulky hardware to be added to the scanning system. To address these issues, a hybrid hardware-software approach was presented in (Pribanić et al., 2016) allowing for fast software registration by using commonly available (smartphone) sensors. In this paper we present hierarchical techniques to improve the performance of this algorithm. Additionally, we compare the performance of our algorithm against other approaches. Experimental results using real data show how the algorithm presented greatly improves the time of the previous algorithm and perform best over all studied algorithms.

本文言語English
ホスト出版物のタイトルVISAPP
編集者Francisco Imai, Alain Tremeau, Jose Braz
出版社SciTePress
ページ44-51
ページ数8
ISBN(電子版)9789897582257
DOI
出版ステータスPublished - 2017
イベント12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2017 - Porto, Portugal
継続期間: 2017 2 272017 3 1

出版物シリーズ

名前VISIGRAPP 2017 - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications
4

Other

Other12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2017
CountryPortugal
CityPorto
Period17/2/2717/3/1

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

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