基于深度卷积网络的单眼图像三维重建

Yinhui Ren, Zhihui Wang, Daoerji Fan
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引用次数: 1

摘要

单目图像的三维重建是机器视觉的重要组成部分。有效地重建物体或场景的三维模型已成为计算机视觉领域的研究热点。在这篇文章中,我们专注于通过单眼图像的深度信息来恢复三维模型。首先,我们使用深度学习来获得单个图像的深度。接下来,根据相机参数从深度图中重建点云,达到三维重建的目的。与传统方法相比,我们的方法更快、更轻松,重构场景的三维信息可以有效地恢复,重建的三维模型也具有更好的真实性。
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3D Reconstruction From Monocular Images Based on Deep Convolutional Networks
3D reconstruction from monocular images is an essential part of machine vision. The effective reconstruction of 3D models of objects or scenes has become a research focus in computer vision. In this article, we concentrate on restoring the 3D model through the depth information of a monocular image. First and foremost, we use deep learning to get the depth of a single image. Next, the point cloud is reconstructed from the depth map according to the camera parameters to achieve the purpose of the 3D reconstruction. Compared with traditional methods, our approach is faster and more relaxed, and the reconstructed three-dimensional information of scenes can be recovered efficiently, our reconstructed 3D models also have better authenticity.
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