Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (4)
  • Open Access


    Advancing Wound Filling Extraction on 3D Faces: An Auto-Segmentation and Wound Face Regeneration Approach

    Duong Q. Nguyen1, Thinh D. Le3, Phuong D. Nguyen3, Nga T. K. Le2, H. Nguyen-Xuan3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 2197-2214, 2024, DOI:10.32604/cmes.2023.043992

    Abstract Facial wound segmentation plays a crucial role in preoperative planning and optimizing patient outcomes in various medical applications. In this paper, we propose an efficient approach for automating 3D facial wound segmentation using a two-stream graph convolutional network. Our method leverages the Cir3D-FaIR dataset and addresses the challenge of data imbalance through extensive experimentation with different loss functions. To achieve accurate segmentation, we conducted thorough experiments and selected a high-performing model from the trained models. The selected model demonstrates exceptional segmentation performance for complex 3D facial wounds. Furthermore, based on the segmentation model, we propose… More > Graphic Abstract

    Advancing Wound Filling Extraction on 3D Faces: An Auto-Segmentation and Wound Face Regeneration Approach

  • Open Access


    3D Face Reconstruction from a Single Image Using a Combined PCA-LPP Method

    Jee-Sic Hur1, Hyeong-Geun Lee1, Shinjin Kang2, Yeo Chan Yoon3, Soo Kyun Kim1,*

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6213-6227, 2023, DOI:10.32604/cmc.2023.035344

    Abstract In this paper, we proposed a combined PCA-LPP algorithm to improve 3D face reconstruction performance. Principal component analysis (PCA) is commonly used to compress images and extract features. One disadvantage of PCA is local feature loss. To address this, various studies have proposed combining a PCA-LPP-based algorithm with a locality preserving projection (LPP). However, the existing PCA-LPP method is unsuitable for 3D face reconstruction because it focuses on data classification and clustering. In the existing PCA-LPP, the adjacency graph, which primarily shows the connection relationships between data, is composed of the e-or k-nearest neighbor techniques. More >

  • Open Access


    Fast Mesh Reconstruction from Single View Based on GCN and Topology Modification

    Xiaorui Zhang1,2,3,*, Feng Xu2, Wei Sun3,4, Yan Jiang2, Yi Cao5

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1695-1709, 2023, DOI:10.32604/csse.2023.031506

    Abstract 3D reconstruction based on single view aims to reconstruct the entire 3D shape of an object from one perspective. When existing methods reconstruct the mesh surface of complex objects, the surface details are difficult to predict and the reconstruction visual effect is poor because the mesh representation is not easily integrated into the deep learning framework; the 3D topology is easily limited by predefined templates and inflexible, and unnecessary mesh self-intersections and connections will be generated when reconstructing complex topology, thus destroying the surface details; the training of the reconstruction network is limited by the… More >

  • Open Access


    Fast Generation of Smooth Implicit Surface Based on Piecewise Polynomial

    Taku Itoh1, Susumu Nakata2

    CMES-Computer Modeling in Engineering & Sciences, Vol.107, No.3, pp. 187-199, 2015, DOI:10.3970/cmes.2015.107.187

    Abstract To speed up generating a scalar field g(x) based on a piecewise polynomial, a new method for determining field values that are indispensable to generate g(x) has been proposed. In the proposed method, an intermediate for generating g(x) does not required, i.e., the field values can directly be determined from given point data. Numerical experiments show that the computation time for determining the field values by the proposed method is about 10.4–12.7 times less than that of the conventional method. In addition, on the given points, the accuracy of g(x) obtained by using the proposed More >

Displaying 1-10 on page 1 of 4. Per Page