Determining Surface Roughness and Shape of Specular Diffuse Lobe Objects Using Photometric Sampling Device
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The photometric sampling method extracts shape and reflectance properties of surfaces by using multiple illumination directions and a single viewing direction. We have previously proposed a recovering algorithm for smooth surfaces. One of the limitations of the previous algorithm is that it cannot recover the shape and roughness of specular lobe dominant surfaces. Surface reflection consists of three components: specular spike, specular lobe, and Lambertian. Among these three components, the previous method only can handle surfaces of the specular spike and the Lambertian. This paper proposes a novel algorithm to recover surface shape and roughness of specular lobe dominant surfaces. An extraction algorithm uses the set of image brightness values measured at each surface point. Each brightness value reflecting surfilcc provides one non-linear image irradiant equation, containing unknown parameters for surface orientation, reflectance and Figure 1: Three component reflection model.
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