Real-time 3D reconstruction method using massive multi-sensor data analysis and fusion

Seoungjae Cho, Kyungeun Cho

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

This paper proposes a method to reconstruct three-dimensional (3D) objects using real-time fusion and analysis of multiple sensor data. This paper attempts to create a realistic 3D visualization with which a remote pilot can intuitively control a remote unmanned robot by utilizing the characteristics of massive sensor data. The 3D reconstruction system proposed in this paper is comprised of 3D and two-dimensional (2D) data segmentation method, a 3D reconstruction method applied to each object, and a projective texture mapping method. Specifically, we propose applying both a 2D region extraction method and a 3D mesh modeling method to each object. The proposed schemes are implemented as a real-time application to verify real-time performance. This paper proves that 3D meshes can be modeled in real time by using the proposed method. The proposed method allows the remote control of a robot for real-time 3D rendering of remote scenes, which is essential for various tasks in areas that cannot be easily accessed by humans.

Original languageEnglish
Pages (from-to)3229-3248
Number of pages20
JournalJournal of Supercomputing
Volume75
Issue number6
DOIs
StatePublished - 1 Jun 2019

Keywords

  • 3D point cloud
  • 3D reconstruction
  • Object segmentation
  • Template mesh
  • Unmanned ground vehicle

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