Towards Full 3D Helmholtz Stereovision Algorithms
Towards Full 3D Helmholtz Stereovision Algorithms
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DOI：
10.1007/978-3-642-19315-6_4
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发表时间：
2010-11
期刊：
影响因子：
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通讯作者：
Amaël Delaunoy;E. Prados;P. Belhumeur
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文献类型：
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作者：
Amaël Delaunoy;E. Prados;P. Belhumeur
Helmholtz立体视觉方法仅限于双目立体视觉或深度图重建。在本文中，我们扩展这些方法恢复完整的三维形状的对象的场景从多视图亥姆霍兹立体视觉。因此，我们能够重建任何任意和未知的双向反射分布函数的对象的完整的三维形状。与以前的方法不同，这可以使用完整的表面表示模型来实现。特别是遮挡（自遮挡以及投射阴影）在曲面优化过程中更容易处理。更确切地说，我们使用三角形网格表示，它允许自然指定场景的一个点的几何形状和它的表面法线之间的关系。我们将展示如何使用相干梯度下降流来实现所提出的方法。各种实例说明了结果和效益。
Helmholtz stereovision methods are limited to binocular stereovision or depth maps reconstruction. In this paper, we extend these methods to recover the full 3D shape of the objects of a scene from multiview Helmholtz stereopsis. Thus, we are able to reconstruct the complete three-dimensional shape of objects made of any arbitrary and unknown bidirectional reflectance distribution function. Unlike previous methods, this can be achieved using a full surface representation model. In particular occlusions (self occlusions as well as cast shadows) are easier to handle in the surface optimization process. More precisely, we use a triangular mesh representation which allows to naturally specify relationships between the geometry of a point of the scene and its surface normal. We show how to implement the presented approach using a coherent gradient descent flow. Results and benefits are illustrated on various examples.