Curved surface fitting using a raster-scanning window for smoothing PCD

Fusaomi Nagata, Norifumi Horie, Keigo Watanabe, Maki K. Habib

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Although point cloud data (PCD) are easily measured using a RGB-Depth sensor such as Kinect and Xtion, measured PCD have undesirable noise and fluctuation of values. In this paper, a curved surface fitting method using a raster-scanning window is proposed to smooth original organized PCD with noise. The method allows PCD to be fitted to numerous small quadratic curved surfaces and to be smoothed while keeping its own shape feature. The effectiveness and usefulness of the proposed system are demonstrated through actual smoothing experiments.

Original languageEnglish
Title of host publication2017 56th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages172-175
Number of pages4
ISBN (Electronic)9784907764579
DOIs
Publication statusPublished - Nov 10 2017
Event56th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2017 - Kanazawa, Japan
Duration: Sep 19 2017Sep 22 2017

Publication series

Name2017 56th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2017
Volume2017-November

Other

Other56th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2017
CountryJapan
CityKanazawa
Period9/19/179/22/17

Keywords

  • Curved surface fitting
  • Least square method
  • PCD
  • Raster scanning window
  • Reverse engineering
  • Smoother

ASJC Scopus subject areas

  • Computer Science Applications
  • Control and Optimization
  • Control and Systems Engineering
  • Instrumentation

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