Deep Neural Network for 3D Shape Classification Based on Mesh Feature

Abstract

Virtual reality, driverless cars, and robotics all make extensive use of 3D shape classification. One of the most popular ways to represent 3D data is with polygonal meshes. In particular, triangular mesh is frequently employed. A triangular mesh has more features than 3D data formats such as voxels, multi-views, and point clouds. The current challenge is to fully utilize and extract useful information from mesh data. In this paper, a 3D shape classification network based on triangular mesh and graph convolutional neural networks was suggested. The triangular face of this model was viewed as a unit. By obtaining an adjacency matrix from mesh data, graph convolutional neural networks can be utilized to process mesh data. The studies were performed on the ModelNet40 dataset with an accuracy of 91.0%, demonstrating that the classification network in this research may produce effective results.

An improved fused feature residual network for 3D point cloud data

“…Table 2 compares the classification accuracy of the proposed method to that of alternative scalable 3D representations techniques on the ModelNet40 datasets. As observed, the proposed method performs better than VoxNet (Maturana and Scherer, 2015 ), 3DGAN (Wu et al, 2016 ), 3DShapeNets (Wu et al, 2015 ), NormalNet, VACWGAN-GP (Wang et al, 2019a ; Ergün and Sahillioglu, 2023 ), DPRNet (Arshad et al, 2019 ), Pointwise (Hua et al, 2018 ), BV-CNN's (Ma et al, 2017 ), NPCEM (Song et al, 2020 ), ECC (Simonovsky and Komodakis, 2017 ), PointNet (Charles et al, 2017 ), Geometry image (Sinha et al, 2016 ), VSL (Liu et al, 2018 ), GIFT (Bai et al, 2016 ), FPNN (Li et al, 2016 ), DGCB-Net (Tian et al, 2020 ), and DeepNN (Gao et al, 2022 ) that utilized mesh 3D data. The recent RECON (Qi et al, 2023 ) and PointConT (Liu et al, 2023 ) slightly outperformed our technique, which could be attributed to their usage of transformers and pre-train models.…”

Camera Path Generation for Triangular Mesh Using Toroidal Patches

“…The digital twin concept has made 3D models a crucial component across various industries, from state-of-the-art IT sectors to traditional manufacturing, as they continue to embrace digital twin technology for innovation. Among the various data structures for these 3D models, the triangular mesh, which comprises a set of vertices (V), edges (E), and triangles (F), stands out as a predominant choice in both industry and academic research [1][2][3][4].…”