“Curvature-aware Adaptive Capture of 3D Geometry and Appearance” by Choi, Lee, Kim, Ahmed, Lee, et al. …

  • ©Junho Choi, Yong Yi Lee, Yong Hwi Kim, Bilal Ahmed, Jong Hun Lee, Moon Gu Son, Junbum Kim, and Kwan H. Lee

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Entry Number: 40

Title:

    Curvature-aware Adaptive Capture of 3D Geometry and Appearance

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Abstract:


    Various vision-based measurement systems have been developed to reconstruct the 3D shape and appearance of an object. To achieve this, a large number of the samples need to be captured. However, most of the existing measurement system requires a long acquisition time because of system complexity. Although some systems present effective acquisition strategy in the adaptive manner, they focus on only 2D planar samples so that they cannot handle complex 3D object and its reflectance property. In this paper, we present the multi-camera and multi-light source based measurement system that capture the 3D geometry and appearance simultaneously. We also proposed a novel curvature-aware acquisition strategy for reducing the acquisition time and data storage requirement. Since the proposed method can efficiently capture the appearance of 3D objects with complicated shape, expect to progress the digitization in the various field such as museum and industry.

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Acknowledgements:


    This work was supported by the MSIP(Ministry of Science, ICT and Future Planning), Korea, under “Development of a smart mixed reality technology for improving the pipe installation and inspection processes in the offshore structure fabrication” (S0602-17-1021) supervised by the NIPA (National IT industry Promotion Agency).


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