Single color image photometric stereo for multi-colored surfaces
Single color image photometric stereo for multi-colored surfaces
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DOI：
10.1016/j.cviu.2018.04.003
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发表时间：
2018-06-01
影响因子：
4.5
通讯作者：
Yamaguchi, Masahiro
中科院分区：
文献类型：
--
作者：
Ozawa, Keisuke;Sato, Imari;Yamaguchi, Masahiro
我们提出了一种只需要单色图像的光度立体方法。传统的单色图像彩色立体测光方法不能处理多色表面，因为在一个表面点上的颜色观测不足以确定该点的反射率和表面法线。我们通过引入表面颜色特征来利用表面颜色和几何形状的全局信息，该特征可以将表面分类为相同颜色的区域并同时估计表面法线。表面颜色特征在几何上是不变的，它限定了RGB反射率平方范数的空间分布，并将反射率范数的表面点属性为正确的颜色。我们讨论了表面分类的理论有效性，并提出了一种实用的多色表面恢复算法。尽管一些分类歧义在原则上仍然存在，但我们表明它们可以在表面几何形状的平滑约束下解决。通过仿真评估了该方法的准确性，并在真实场景中验证了其有效性。
We present a photometric stereo method that requires only a single color image. Conventional color photometric stereo methods for single color images cannot deal with multi-colored surfaces, since a color observation at a surface point is insufficient for determining the reflectances and the surface normal at that point. We exploit the global information of surface color and geometry by introducing a surface-color feature that enables classification of a surface into regions of the same color and simultaneously estimate surface normals. The surface-color feature, being invariant in geometry, qualifies the spatial distribution of the square norm of RGB reflectances and attributes surface points of a reflectance norm to the correct color. We discuss the theoretical validity of our surface classification and present a practical algorithm for multi-colored surface recovery. Although some classification ambiguities remain in principle, we show that they can be resolved under a smoothness constraint on the surface geometry. We evaluated the accuracy of our method through simulations and we demonstrated its effectiveness on real scenes.