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3D Scene Reconstruction from Multi-aperture Images

机译:从多孔径图像重建3D场景

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摘要

With the development of virtual reality, there is a growing demand for 3D modeling of real scenes. This paper proposes a novel 3D scene reconstruction framework based on multi-aperture images. Our framework consists of four parts. Firstly, images with different apertures are captured via programmable aperture. Secondly, we use SIFT method for feature point matching. Then we exploit binocular stereo vision to calculate camera parameters and 3D positions of matching points, forming a sparse 3D scene model. Finally, we apply patch-based multi-view stereo to obtain a dense 3D scene model. Experimental results show that our method is practical and effective to reconstruct dense 3D scene.
机译:随着虚拟现实的发展,对真实场景的3D建模的需求不断增长。本文提出了一种基于多孔径图像的新颖的3D场景重建框架。我们的框架包括四个部分。首先,通过可编程光圈捕获具有不同光圈的图像。其次,我们使用SIFT方法进行特征点匹配。然后,我们利用双目立体视觉来计算相机参数和匹配点的3D位置,从而形成稀疏的3D场景模型。最后,我们应用基于补丁的多视图立体声以获得密集的3D场景模型。实验结果表明,该方法对于重建密集的3D场景是切实可行的。

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