Showing papers on "Illumination problem published in 2003"

Face representation under different illumination conditions

Abstract: To deal with image variations due to illumination problem, recently Ramamoorthi and Basri have independently derived a spherical harmonic analysis for the Lambertian reflectance and linear subspace. Their theoretical work provided a new approach for face representation, however both of them had the assumption that the 3D surface normal and albedo are known. This assumption limits this algorithm's application. In this paper, we present a novel method for modeling 3D face shape and albedo from only three images with unknown light directions and this work well fills the blank, which Ramamoorthi and Basri left. By taking the advantage of similar 3D shape of all human faces, the highlight of the new method is that it circumambulates the linear ambiguity by 3D alignment. The experiment results show that our estimated model can be perfectly employed to face recognition and 3D reconstruction.

Face representation and reconstruction under different illumination conditions

Abstract: To deal with image variations due to illumination problem, Ramamoorthi and Basri have independently derived a spherical harmonic analysis for the Lambertian reflectance and linear subspace. Their theoretical work provided a new approach for face representation, however both of them assume that the 3D surface normals and albedo (or unit albedo) are known, which limit this algorithm's application. We present a novel method for modelling 3D face shape and albedo from only three images and this work will fill the blank which Ramamoorthi and Basri left. Our work is closely related to photometric stereo, but conditions of photometric stereo for estimating albedo and surface normal are too strict to be applied for real application. Moreover, the conventionally used singular value decomposition (SVD) approach leads to the notorious linear ambiguity and the solution to this problem needs to introduce more constraints or more images. By taking advantage of similar 3D shape of all human faces, the highlight of the new method is that it circumambulates the linear ambiguity by 3D alignment. The experiment results show that our estimated model can be perfectly employed to face recognition and 3D reconstruction.

A Heuristic Algorithm: Simulating Light Propagation in Orthogonal Polygons

Abstract: The purpose of this study is to determine the area of light emitted by a source in an orthogonal polygon on a two-dimensional lattice using the cellular automata construction method. By applying this method, an efficient algorithm was tested and developed to determine the area of light propagated. The algorithm, although not optimal, gives a close approximation of the number of cells on the lattice that are to be illuminated. Furthermore, the algorithm acknowledged in this research is sufficient to work with any orthogonal polygon. This research is based on a classical computational geometry problem – the art gallery problem. It is hoped that the results of this research can contribute to finding more efficient solutions to the problem as well as other computational geometry problems. Introduction In 1973 during a discussion with other mathematicians, Victor Klee introduced the art gallery problem: How many guards are sufficient to guard any polygon with n vertices? The problem was called the art gallery problem or the illumination problem because it resembled a security configuration in an art gallery as well as represented the illumination of an art gallery. For example, if an owner of an art gallery wants to place cameras (source of light) such that the whole gallery will be thief proof, before that owner can configure his/her security setup, he or she will first have to answer a few questions. Questions like “What is the minimum number of cameras required in order to protect the expensive art collection?” and “Where will the cameras be placed so that the whole gallery is guarded?” There are many forms of the art gallery problem, dealing with many types of polygons. In this research we looked only at using orthogonal polygons to represent a gallery. Orthogonal polygons are polygons that have a set of mutually perpendicular axis, meeting at right angles (see fig. 1). An orthogonal polygon can also be dissected at its vertexes, resulting in squares or rectangles. GVSU McNair Scholars Journal VOLUME 7, 2003 91 A Heuristic Algorithm: Simulating Light Propagation in Orthogonal Polygons