Object classification with range and reflectance data from a single laser scanner

Shuji Oishi, Naoaki Kondo, Ryo Kurazume

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

Abstract

This paper presents a new object classification technique for 3D point cloud data acquired with a laser scanner. In general, it is not straightforward to distinguish objects that have similar 3D structures but belong to different categories based only on the range data. To tackle this issue, we focus on laser reflectance obtained as a side product of range measurement by a laser scanner. Since laser reflectance contains appearance information, the proposed method classifies objects based on not only geometrical features in range data but also appearance features in reflectance data, both of which are acquired by a single laser scanner. Furthermore, we extend the conventional Histogram of Oriented Gradients (HOG) so that it couples geometrical and appearance information more tightly. Experiments show the proposed technique combining geometrical and appearance information outperforms conventional techniques.

Original languageEnglish
Title of host publicationThirteenth International Conference on Quality Control by Artificial Vision 2017
EditorsAtsushi Yamashita, Hajime Nagahara, Kazunori Umeda
PublisherSPIE
ISBN (Electronic)9781510611214
DOIs
Publication statusPublished - Jan 1 2017
Event13th International Conference on Quality Control by Artificial Vision, QCAV 2017 - Tokyo, Japan
Duration: May 14 2017May 16 2017

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume10338
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Other

Other13th International Conference on Quality Control by Artificial Vision, QCAV 2017
CountryJapan
CityTokyo
Period5/14/175/16/17

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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  • Cite this

    Oishi, S., Kondo, N., & Kurazume, R. (2017). Object classification with range and reflectance data from a single laser scanner. In A. Yamashita, H. Nagahara, & K. Umeda (Eds.), Thirteenth International Conference on Quality Control by Artificial Vision 2017 [103380M] (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 10338). SPIE. https://doi.org/10.1117/12.2265178