3D Digital Image Virtual Scene Reconstruction Algorithm Based on Machine Learning

被引：0
|
作者：
Xie, Yiyi [1 ]
机构：
[1] School of Engineering, Guangzhou College of Technology and Business, Guangzhou,510000, China
来源：
International Journal for Engineering Modelling | 2024年 / 37卷 / 02期
关键词：
3D modeling has been widely used in industrial; medical; military and other fields. Trying to solve the issue that the traditional 3D reconstruction model is ineffective in processing digital image feature extraction in virtual scenes; this study adopts a multi-view stereo vision algorithm and neural network to optimize it based on the traditional 3D reconstruction algorithm. Then; the spatial attention mechanism and the channel attention mechanism were combined to generate a Convolutional Block Attention Module (CBAM) model; and the CBAM was used in a multi-view stereo vision algorithm model. The model's performance is tested; and it is found that the convergence speed is faster in training; the loss function value is lower; and the overall model's performance is better. In the test; compared with the other three models; the accuracy of the proposed model is improved by 17%; 9% and 3% on average. The integrity of MVSNet-CBAM was enhanced by 28%; 14%; and; 9%; respectively. The experiment verifies the validity; which aims to provide a reference for 3D digital image virtual scene reconstruction. © 2024; University of Split. All rights reserved;
D O I：
10.31534/engmod.2024.2.ri.02f
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页码：23 / 40
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