Surface Reflectance and Shape from Images Using Collinear Light Source Jiping Lu Jim Little firstname.lastname@example.org email@example.com Laboratory for Computational Intelligence Department of Computer Science The University of British Columbia Vancouver BC Canada V6T 1Z4
ABSTRACT The purpose of computer vision is to extract useful information from images. Image features such as occluding contours, edges, flow, brightness, and shading provide geometric and photometric constraints on the surface shape and reflectance of physical objects in the scene. In this thesis, two novel tech- niques are proposed for surface reflectance extraction and surface recovery. They integrate geometric and photometric constraints in images of a rotating object illuminated under a collinear light source (where the illuminant direc- tion of the light source lies on or near the viewing direction of the camera). The rotation of the object can be precisely controlled. The object surface is assumed to be $C^2$ and its surface reflectance function is uniform. The first technique, called the photogeometric technique, uses geometric and photometric constraints on surface points with surface normal perpendicular to the image plane to calculate 3D locations of surface points, then extracts the surface reflectance function by tracking these surface points in the images. Using the extracted surface reflectance function and two images of the surface, the technique recovers the depth and surface orientation of the object surface simultaneously. The second technique, named the wire-frame technique, further exploits geome- tric and photometric constraints on the surface points whose surface normals are coplanar with the viewing direction and the rotation axis to extract a set of 3D curves. The set of 3D curves comprises a wire frame on the surface. The depth and surface orientation between curves on the wire frame are interpolated by using geometric or photogeometric methods. The wire-frame technique is superior because it does not need the surface reflectance function to extract the wire frame. It also works on piecewise uniform surfaces and requires only that the light source be coplanar with the viewing direction and the rotation axis. In addition, by interpolating the depth and surface orientation from a dense wire frame, the surface recovered is more accurate. The two techniques have been tested on real images of surfaces with differ- ent reflectance properties and geometric structures. The experimental results and comprehensive analysis show that the proposed techniques are efficient and robust. As an attempt to extend our research to computer graphics, work on extracting the shading function from real images for graphics rendering shows some promising results. Key words: Physics based vision, Reflectance, Shape recovery, Integrating mul- tiple cues, Integrating multiple views, surface modeling, surface rendering.
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