APPLIED LASER, Volume. 45, Issue 1, 194(2025)

The 3D Reconstruction Method Based on Multi-View Close-Range Images of the Yimeng Small Cotton Padded Coat

Wu Yunze1... Wang Jian1,2,*, Zhang Zhenyu1 and Wu Zhaojing3 |Show fewer author(s)
Author Affiliations
  • 1College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, Shandong, China
  • 2Qingdao Key Laboratory of Beidou Navigation and Intelligent Spatial Information Technology Application, Qingdao 266590, Shandong, China
  • 3Yimeng Small Cotton Padded Coat Folk Culture Park, Linyi 276412, Shandong, China
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    The Yimeng small cotton padded coat, recognized as a traditional attire of the Yimeng area and designated as an Intangible Cultural Heritage by Shandong Province, currently faces an urgent challenge of craft preservation due to the advancing age of its principal artisans and the absence of a structured inheritance system. This study employs digital technology to address this issue, utilizing multi-view close-range images for the reconstruction of the Yimeng coat. The research applies the Alpha-shape algorithm and Poisson disk resampling algorithm to refine point cloud data, yielding a highly accurate and realistic 3D model. Validation confirms that the generated 3D models satisfy the necessary accuracy standards. The proposed 3D reconstruction method offers a cost-effective, accurate, efficient, and visual approach that successfully retains the traditional craft elements such as textures and patterns of the Yimeng coat. Consequently, this method enhances production quality and authenticity in retail, while also providing data that supports digital customization and virtual fitting.

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    Wu Yunze, Wang Jian, Zhang Zhenyu, Wu Zhaojing. The 3D Reconstruction Method Based on Multi-View Close-Range Images of the Yimeng Small Cotton Padded Coat[J]. APPLIED LASER, 2025, 45(1): 194

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    Paper Information

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    Received: May. 21, 2023

    Accepted: Apr. 17, 2025

    Published Online: Apr. 17, 2025

    The Author Email: Wang Jian (wangj@sdust.edu.cn)

    DOI:10.14128/j.cnki.al.20254501.194

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