吉林大学学报(理学版) ›› 2023, Vol. 61 ›› Issue (6): 1425-1431.

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基于机器学习的三维数字图像虚拟场景重建算法

宗敏   

  1. 韩国清州大学 艺术学院, 韩国 清州 28497;  潍坊学院 传媒学院, 山东 潍坊 261061
  • 收稿日期:2023-01-13 出版日期:2023-11-26 发布日期:2023-11-20
  • 通讯作者: 宗敏 E-mail:zongmin010@163.com

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

ZONG Min   

  1. College of Arts, Kyeongju University, Kyeongju 28497, Korea; School of Communication, Weifang University, Weifang 261061, Shandong Province, China
  • Received:2023-01-13 Online:2023-11-26 Published:2023-11-20

摘要: 为使三维数字图像虚拟场景重建可以获得更优质的画面, 提出一种基于机器学习的三维数字图像虚拟场景重建算法. 首先分析场景的状态信息和呈现指令, 得到图像重构的网格模型顶点分布位置, 通过局部坐标法近似计算全局图像, 校正局部细节, 完成三维数字图像的渲染处理; 然后以空间和尺度为特征点, 在图像上构建窗口检测模板, 应用分类器抑制离散特征点, 去除冗余特征; 最后根据拟合函数法求出平滑后的三维坐标重建三维曲面, 将局部二维三角分割并映射到三维空间, 实现三维数字图像虚拟场景重建. 实验结果表明, 该算法收敛速度较快, 重建图像细节和边缘轮廓完整, 整体效果较好.

关键词: 三维数字图像, 机器学习, 虚拟场景重建, 数字图像处理, 特征提取

Abstract: In order to achieve  more high-quality images in 3D digital image virtual scene  reconstruction, the author proposed  a 3D digital image virtual scene reconstruction algorithm based on machine learning. Firstly, the state information and presentation instructions of the scene were analyzed to obtain the vertex distribution positions of the mesh model for image reconstruction. The global image was approximately calculated by local coordinate method, and the local details were corrected to complete the rendering processing of 3D digital images. Secondly, taking space and scale as feature points, a window detection template was constructed on the image, and a classifier was used to suppress discrete feature points and remove redundant features. Finally, according to the fitting function method, the smoothed 3D coordinates were obtained  to reconstruct the 3D surface, and the local 2D triangle was segmented and mapped to the 3D space to realize the 3D digital image virtual scene reconstruction. The experimental results show that the proposed algorithm converges faster, the reconstructed image details and edge contours are complete, and the overall effect is good.

Key words: three-dimensional digital image, machine learning, virtual scene reconstruction, digital image processing, feature extraction

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