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RGB-D SLAM Based Incremental Cuboid Modeling

  • Masashi MishimaEmail author
  • Hideaki Uchiyama
  • Diego Thomas
  • Rin-ichiro Taniguchi
  • Rafael Roberto
  • João Paulo Lima
  • Veronica Teichrieb
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11129)

Abstract

This paper present a framework for incremental 3D cuboid modeling combined with RGB-D SLAM. While performing RGB-D SLAM, planes are incrementally reconstructed from point clouds. Then, cuboids are detected in the planes by analyzing the positional relationships between the planes; orthogonality, convexity, and proximity. Finally, the position, pose and size of a cuboid are determined by computing the intersection of three perpendicular planes. In addition, the cuboid shapes are incrementally updated to suppress false detections with sequential measurements. As an application of our framework, an augmented reality based interactive cuboid modeling system is introduced. In the evaluation at a cluttered environment, the precision and recall of the cuboid detection are improved with our framework owing to stable plane detection, compared with a batch based method.

Keywords

Geometric shape Cuboid Incrementally structural modeling Point cloud 

Notes

Acknowledgment

This work is supported by JSPS KAKENHI Grant Number JP17H01768.

Supplementary material

Supplementary material 1 (mp4 49230 KB)

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Masashi Mishima
    • 1
    Email author
  • Hideaki Uchiyama
    • 1
  • Diego Thomas
    • 1
  • Rin-ichiro Taniguchi
    • 1
  • Rafael Roberto
    • 2
  • João Paulo Lima
    • 2
    • 3
  • Veronica Teichrieb
    • 2
  1. 1.Kyushu UniversityFukuokaJapan
  2. 2.Universidade Federal de PernambucoRecifeBrazil
  3. 3.Universidade Federal Rural de PernambucoRecifeBrazil

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