3DMRRC: 3D Mesh Reconstruction using Ray Casting for stationary subjects

Swathy Nair, Om Shah, K. Devadkar
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Abstract

With increasing processing power and better rendering capabilities, it is now feasible to view a 3D mesh of millions of triangles. It has various application domains such as augmented preview, medical field, construction and many more. However, creating such a detailed mesh requires manually modelling each feature in a tool (like Blender). A quicker approach would be to use photogrammetry that requires a set of cameras capturing each visual aspect of the subject from specific angles. As we can observe, both of these techniques are resource intensive (time and physical camera setup respectively). Further, Deep learning based methods have been proposed, but these do not work on novel geometry. We propose a methodology that makes use of the unique approach of ray casting which takes image sequences as an input and produce a 3 dimensional mesh. This approach can work for any novel geometry since no pre-learning is being performed as well as the time taken would be far less than manual modelling and also works with a single camera setup.
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3DMRRC:使用光线投射对静止物体进行三维网格重建
随着处理能力的提高和更好的渲染能力,现在可以查看数百万个三角形的3D网格。它具有各种应用领域,如增强预览,医疗领域,建筑等。然而,创建如此详细的网格需要在工具(如Blender)中手动建模每个特征。一种更快的方法是使用摄影测量法,它需要一组相机从特定的角度捕捉拍摄对象的每个视觉方面。正如我们所观察到的,这两种技术都是资源密集型的(分别是时间和物理摄像机设置)。此外,已经提出了基于深度学习的方法,但这些方法不适用于新的几何形状。我们提出了一种利用独特的光线投射方法的方法,该方法将图像序列作为输入并产生三维网格。这种方法可以适用于任何新的几何形状,因为不需要进行预学习,而且所花费的时间远远少于手动建模,并且可以使用单个相机设置。
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