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author:

Fang, Wei (Fang, Wei.) [1] | Zheng, Lianyu (Zheng, Lianyu.) [2] | He, Bingwei (He, Bingwei.) [3] (Scholars:何炳蔚) | Wang, Qing (Wang, Qing.) [4]

Indexed by:

Scopus SCIE

Abstract:

Three-dimensional (3D) model acquisition is the process of building a 3D model of an object. But due to the limited field of view of the scanner, this task is mainly performed by taking several scans with human intervention. In order to make the 3D modeling process efficient, a novel automatic 3D modeling method for unknown objects based on hybrid vision technology in a binocular structured light system (BSLS) is proposed. Firstly, the limit visual vacuums of the BSLS are established, and they will be used to predict the unknown area with an acquired 2.5D range image. With the 2D intensity image acquired synchronously, the coarse boundary size is recovered from Shape from Shading, and it leads the prediction of the unknown area to be more precise. Based on the combination of the predicted contours, the next best viewpoint is determined with more unknown areas visible. The proposed method can be used to obtain the 3D models of unknown objects automatically, and the experimental results illustrate the validity and efficiency of our approach.

Keyword:

3D modeling Binocular structured light Hybrid vision technology Viewpoint planning

Community:

  • [ 1 ] [Fang, Wei]Beihang Univ, Sch Mech Engn & Automat, Xueyuan Rd, Beijing 100191, Peoples R China
  • [ 2 ] [Zheng, Lianyu]Beihang Univ, Sch Mech Engn & Automat, Xueyuan Rd, Beijing 100191, Peoples R China
  • [ 3 ] [He, Bingwei]Fuzhou Univ, Sch Mech Engn & Automat, Xueyuan Rd, Fuzhou 350116, Peoples R China
  • [ 4 ] [Wang, Qing]Univ Durham, Sch Engn & Comp Sci, South Rd, Durham DH1 3LE, England

Reprint 's Address:

  • [Zheng, Lianyu]Beihang Univ, Sch Mech Engn & Automat, Xueyuan Rd, Beijing 100191, Peoples R China

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Source :

INTERNATIONAL JOURNAL OF PRECISION ENGINEERING AND MANUFACTURING

ISSN: 2234-7593

Year: 2017

Issue: 3

Volume: 18

Page: 275-284

1 . 6 6 1

JCR@2017

2 . 6 0 0

JCR@2023

ESI Discipline: ENGINEERING;

ESI HC Threshold:177

JCR Journal Grade:3

CAS Journal Grade:4

Cited Count:

WoS CC Cited Count: 4

SCOPUS Cited Count: 7

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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