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A generic and provably convergent shape-from-shading method for orthographic and pinhole cameras

机译:适用于正交摄影和针孔相机的通用且可证明收敛的从阴影生成形状的方法

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We describe a mathematical and algorithmic study of the Lambertian "Shape-From-Shading" problem for orthographic and pinhole cameras. Our approach is based upon the notion of viscosity solutions of Hamilton-Jacobi equations. This approach provides a mathematical framework in which we can show that the problem is well-posed (we prove the existence of a solution and we characterize all the solutions). Our contribution is threefold. First, we model the camera both as orthographic and as perspective (pinhole), whereas most authors assume an orthographic projection (see Horn and Brooks (1989) for a survey of the SFS problem up to 1989 and Zhang et al. (1999), Kozera (1998), Durou et al. (2004) for more recent ones); thus we extend the applicability of shape from shading methods to more realistic acquisition models. In particular it extends the work of Prados et al. (2002a) and Rouy and Tourin (1992). We provide some novel mathematical formulations of this problem yielding new partial differential equations. Results about the existence and uniqueness of their solutions are also obtained. Second, by introducing a "generic" Hamiltonian, we define a general framework allowing to deal with both models (orthographic and perspective), thereby simplifying the formalization of the problem. Thanks to this unification, each algorithm we propose can compute numerical solutions corresponding to all the modeling. Third, our work allows us to come up with two new generic algorithms for computing numerical approximations of the "continuous solution of the "Shape-From-Shading" problem as well as a proof of their convergence toward that solution. Moreover, our two generic algorithms are able to deal with discontinuous images as well as images containing black shadows.
机译:我们描述了用于正交摄影和针孔摄影机的Lambertian“从阴影形成形状”问题的数学和算法研究。我们的方法基于Hamilton-Jacobi方程的粘度解的概念。这种方法提供了一个数学框架,在该框架中,我们可以证明问题是正当的(我们证明了解决方案的存在,并对所有解决方案进行了描述)。我们的贡献是三倍。首先,我们将相机建模为正射和透视(针孔),而大多数作者都采用正射投影(请参见Horn和Brooks(1989)来调查直到1989年的SFS问题以及Zhang等(1999), Kozera(1998),Durou等(2004)的最新文章);因此,我们将形状的适用性从阴影方法扩展到更实际的采集模型。特别是它扩展了Prados等人的工作。 (2002a)和Rouy and Tourin(1992)。我们提供了这个问题的一些新颖的数学公式,产生了新的偏微分方程。还获得了有关其解的存在性和唯一性的结果。其次,通过引入“通用”哈密顿量,我们定义了一个允许处理两种模型(正交和透视)的通用框架,从而简化了问题的形式化过程。由于这种统一,我们提出的每种算法都可以计算与所有建模相对应的数值解。第三,我们的工作允许我们提出两种新的通用算法,用于计算“从阴影开始”问题的连续解的数值逼近,以及它们向该解收敛的证明。该算法能够处理不连续的图像以及包含黑色阴影的图像。

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