Alignment of point cloud data acquired from continuous view points on flat surface

Kenta Ochiai, Masafumi Nakagawa

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

Abstract

A three-dimensional point cloud data measured with terrestrial 3D scanner is suitable for a spatial representation in a plant management, disaster monitoring and verification in traffic accident. Moreover, the latest 3D scanners can acquire massive point cloud data in wide range for a short time. However, 3D data measured in outdoor environment contains optical errors caused by a mirror reflection and point noises caused by movers. Therefore, generally, an additional 3D measurement is conducted and the additional data are integrated to an initial measured point cloud data with a procedure of 3D data alignment. Moreover, conventional 3D alignment methodology requires geometrical features. In other words, these approaches are limited to uneven surface. Therefore, a flat surface is a difficult object for the conventional data alignment methodology. In our experiment, Time-of-Flight camera was used as a handheld 3D scanner. Moreover, we used infrared images taken from the camera as feature values. Then, we conducted an alignment of point cloud data acquired from continuous view points on flat surfaces. Additionally, we have confirmed that our approach can integrate point cloud data even if measured object is a flat surface.

Original languageEnglish
Title of host publication33rd Asian Conference on Remote Sensing 2012, ACRS 2012
Pages1666-1671
Number of pages6
Publication statusPublished - 2012 Dec 1
Event33rd Asian Conference on Remote Sensing 2012, ACRS 2012 - Pattaya, Thailand
Duration: 2012 Nov 262012 Nov 30

Publication series

Name33rd Asian Conference on Remote Sensing 2012, ACRS 2012
Volume2

Conference

Conference33rd Asian Conference on Remote Sensing 2012, ACRS 2012
CountryThailand
CityPattaya
Period12/11/2612/11/30

Keywords

  • Flat surface
  • Handheld 3D scanner
  • Iterative Closest Point (ICP)
  • Simultaneous Localization and Mapping (SLAM)

ASJC Scopus subject areas

  • Information Systems

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