Institute of Computing, State University of Campinas, 13984-971 Campinas, Brazil.
IEEE Trans Image Process. 2011 Dec;20(12):3495-507. doi: 10.1109/TIP.2011.2159386. Epub 2011 Jun 13.
In this paper, we describe a data structure and an algorithm to accelerate the table lookup step in example-based multiimage photometric stereo. In that step, one must find a pixel of a reference object, of known shape and color, whose appearance under m different illumination fields is similar to that of a given scene pixel. This search reduces to finding the closest match to a given m-vector in a table with a thousand or more m-vectors. Our method is faster than previously known solutions for this problem but, unlike some of them, is exact, i.e., always yields the best matching entry in the table, and does not assume point-like sources. Our solution exploits the fact that the table is in fact a fairly flat 2-D manifold in m-dimensional space so that the search can be efficiently solved with a uniform 2-D grid structure.
在本文中，我们描述了一种数据结构和算法，以加速基于示例的多图像光度立体学法中的表查找步骤。在该步骤中，必须找到一个已知形状和颜色的参考对象的像素，其在 m 个不同照明场下的外观与给定场景像素相似。此搜索可归结为在具有一千个或更多 m-向量的表中找到与给定 m-向量最接近的匹配项。我们的方法比以前已知的此类问题的解决方案更快，但与其中一些方法不同的是，它是精确的，即始终在表中返回最佳匹配项，并且不假设点源。我们的解决方案利用了这样一个事实，即该表实际上是 m 维空间中的一个相当平坦的 2-D 流形，因此可以使用均匀的 2-D 网格结构有效地解决搜索问题。
