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Improved shape from shading without initial information

机译:无需初始信息即可从阴影中改善形状

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摘要

The number of constraints imposed on the surface, the light source, the camera model and in particular the initial information makes shape from shading (SFS) very difficult for real applications. There are a considerable number of approaches which require an initial data about the 3D object such as boundary conditions (BC). However, it is difficult to obtain these information for each point of the object Edge in the image, thus the application of these approaches is limited. This paper shows an improvement of the Global View method proposed by Zhu and Shi [1]. The main improvement is that we make the resolution done automatically without any additional information on the 3D object. The method involves four steps. The first step is to determine the singular curves and the relationship between them. In the second step, we generate the global graph, determine the sub-graphs, and determine the partial and global configuration. The proposed method to determine the convexity and the concavity of the singular curves is applied in the third step. Finally, we apply the Fast-Marching method to reconstruct the 3D object. Our approach is successfully tested on some synthetic and real images. Also, the obtained results are compared and discussed with some previous methods.
机译:施加在表面,光源,相机模型上的约束的数量,尤其是初始信息,使得对于实际应用而言,阴影形成的形状(SFS)非常困难。有许多方法需要有关3D对象的初始数据,例如边界条件(BC)。然而,难以针对图像中的对象边缘的每个点获得这些信息,因此这些方法的应用受到限制。本文展示了Zhu和Shi [1]提出的全局视图方法的改进。主要改进在于,我们无需3D对象的任何其他信息即可自动完成分辨率。该方法包括四个步骤。第一步是确定奇异曲线及其之间的关系。在第二步中,我们生成全局图,确定子图,并确定部分和全局配置。第三步采用提出的确定奇异曲线的凸度和凹度的方法。最后,我们应用快速前进方法来重建3D对象。我们的方法已在一些合成和真实图像上成功测试。而且,将获得的结果与一些先前的方法进行比较和讨论。

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