Dense estimation of surface reflectance parameters from registered range and color images by determining illumination conditions

Takashi Machida; Haruo Takemura; Naokazu Yokoya

doi:10.1117/12.424897

13 April 2001 Dense estimation of surface reflectance parameters from registered range and color images by determining illumination conditions

Takashi Machida, Haruo Takemura, Naokazu Yokoya

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Proceedings Volume 4298, Three-Dimensional Image Capture and Applications IV; (2001) https://doi.org/10.1117/12.424897
Event: Photonics West 2001 - Electronic Imaging, 2001, San Jose, CA, United States

Abstract

A texture image has often been used to reproduce real objects in computer graphics (CG). However, the appearance of the object is not reproduced appropriately when lighting conditions of real and CG environments are not consistent. To overcome the problem, we propose a new method for estimating non-uniform reflectance properties which consist of diffuse reflectance, specular reflectance, and surface roughness parameters with convex and concave surface. Such a surface reflectance estimation requires object surface normal, light source position, camera position, and surface color under different illumination conditions for each surface point (pixel). Therefore, we use a laser rangefinder which takes accurately registered range and color images of an object. It is difficult to estimate a specular reflectance parameter, since the specular reflection is observed only within a fixed range of angles among the camera, light source, and viewing position. In our method, an algorithm is proposed to determine light source positions with which the specular reflection component is strongly observed over the surface. We also consider a self shadow and make calculation stable by separating two reflection components. The Torrance-Sparrow model, which accurately represents object reflectance properties, is employed to estimate reflectance parameters by using color images under multiple illumination conditions. In our experiments, a measured object has partially different specular reflection and surface roughness parameters. Experiments show the usefulness of the proposed method.

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Takashi Machida, Haruo Takemura, and Naokazu Yokoya "Dense estimation of surface reflectance parameters from registered range and color images by determining illumination conditions", Proc. SPIE 4298, Three-Dimensional Image Capture and Applications IV, (13 April 2001); https://doi.org/10.1117/12.424897

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KEYWORDS

Reflectivity

Reflection

Specular reflections

Light sources

Surface roughness

Light sources and illumination

RGB color model

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