, our method can be applied to the objects whose chromaticity and albedo are both spatially varying. Our approach solves the problem of shadow, specular reflection, and channel crosstalk. We use the example-based photometric stereo to solve the problem of the color photometric stereo. In this paper, the problem faced by the color photometric stereo method is solved using a different approach from those used in previous studies. The example-based photometric stereo is used for a conventional photometric stereo problem, which assumes the same albedo for each light and is not used for the color photometric stereo problem since the albedo differs for each light. If the appearances of the pixels among those two types of objects are the same, these pixels might have the same surface normal. They assume that the material properties of the objects in the database and the objects to be measured are the same. Those methods capture some images of objects with known shapes. This assumption enables a color photometric stereo to be applied to multicolored objects that can be segmented for each colored region.Įxample-based photometric stereos estimate the surface normal using a database search. assumed that a certain limited area has the same albedo. , using the shape from other methods such as multiview stereo enables the color photometric stereo to be applied to multicolored objects. They estimate the surface normal without disturbing the human eye’s appearance. Each of the three lights has a different spectral distribution, which can be distinguished by the six-band camera. The target objects are observed by a six-band camera. used three lights that can be recognized as white color by the human eye. These methods cannot estimate the surface normal from a single image thus, the optical flow method is used to track the identical point on the object surface among multiple images. Some methods use multiple images to apply a color photometric stereo to multicolored objects. This is an inevitable problem as long as lights are illuminated from colored light sources to estimate the surface normal. The major problem of the color photometric stereo method is the fact that it can only be used with white objects. However, the color photometric stereo has many problems. Such a one-shot photograph enables the measurement of a dynamic object. The color photometric stereo takes one picture with an RGB color camera under red, green, and blue light sources.
This problem can be resolved using the color photometric stereo method (also known as shape-from-color). Therefore, it is impossible to measure a dynamic object. Unlike shape-from-shading, which uses one image, the photometric stereo captures three images with different light source directions. The shape-from-shading method and the photometric stereo method estimate the surface normal of an object by illuminating the object and analyzing the resulting shadings on the object’s surface. To demonstrate the effectiveness of this study, a measurement device that can realize the multispectral photometric stereo method with sixteen colors is employed instead of the classic color photometric stereo method with three colors. The process of our method is pixelwise thus, the estimated surface normal is not oversmoothed, unlike existing methods that use smoothness constraints.
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Color photometric stereos suffer from mathematical difficulty, and they add many assumptions and constraints however, the example-based photometric stereo is free from such mathematical problems. The example-based photometric stereo searches the surface normal from the database of the images of known shapes.
This paper uses an example-based photometric stereo to solve the problem of the color photometric stereo. However, the conventional color photometric stereo cannot estimate a multicolored object due to the colored illumination. As a result, a color photometric stereo can obtain the surface normal of a dynamically moving object from a single image. A photometric stereo needs three images taken under three different light directions lit one by one, while a color photometric stereo needs only one image taken under three different lights lit at the same time with different light directions and different colors.
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