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Automatic 3D model acquisition for unknown objects based on hybrid vision technology

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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.

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Authors and Affiliations

  1. School of Mechanical Engineering and Automation, Beihang University, Xueyuan road, HaiDian region, Beijing, 100191, China

    Wei Fang & Lianyu Zheng

  2. School of Mechanical Engineering and Automation, Fuzhou University, Xueyuan road, MinHou region, Fuzhou, 350116, China

    Bingwei He

  3. School of Engineering and Computing Sciences, Durham University, South Road, Durham, DH1 3LE, UK

    Qing Wang

Authors
  1. Wei Fang
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  2. Lianyu Zheng
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  3. Bingwei He
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  4. Qing Wang
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Correspondence to Lianyu Zheng.

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Fang, W., Zheng, L., He, B. et al. Automatic 3D model acquisition for unknown objects based on hybrid vision technology. Int. J. Precis. Eng. Manuf. 18, 275–284 (2017). https://doi.org/10.1007/s12541-017-0035-2

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  • DOI: https://doi.org/10.1007/s12541-017-0035-2

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