DETERMINING SHAPE AND REFLECTANCE OF HYBRID SURFACES BY PHOTOMETRIC SAMPLING

Machine vision can benefit greatly from the development and utilization of accurate reflectance models. Our hybrid reflectance model is a linear combination of Lambertian and specular components and is obtained from the primary reflection components by making surface assumptions. Hence, Lambertian and specular surfaces are special instances of hybrid surfaces. We present a method for determining the shapes of hybrid surfaces without prior knowledge of the relative strengths of the Lambertian and specular components of reflection. The object surface is illuminated using extended light sources and is viewed from a single direction. Surface illumination using extended sources makes it possible to ensure the detection of both Lambertian and specular reflections. Uniformly distributed source directions are used to obtain an image sequence of the object. This method of obtaining photometric measurements is called photometric sampling. An extraction algorithm uses the set of image intensity values measured at each surface point to compute orientation as well as relative strengths of the Lambertian and specular reflection components. The simultaneous recovery of shape and reflectance parameters enables the method to adapt to variations in reflectance properties from one scene point to another. Experiments were conducted on Lambertian surfaces, specular surfaces, and hybrid surfaces. The measured surface orientations are found to be highly accurate, and the estimated reflectance parameters are consistent with the reflectance characteristics of the surfaces. © 1990 IEEE