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Geometric distributions for catadioptric sensor design
Hicks, R.A.   Perline, R.K.  
Dept. of Math. & Comput. Sci., Drexel Univ., Philadelphia, PA, USA;

This paper appears in: Computer Vision and Pattern Recognition, 2001. CVPR 2001. Proceedings of the 2001 IEEE Computer Society Conference on
Publication Date: 2001
Volume: 1,  On page(s): I-584- I-589 vol.1
ISSN: 1063-6919
ISBN: 0-7695-1272-0
INSPEC Accession Number: 7176908
Digital Object Identifier: 10.1109/CVPR.2001.990526
Current Version Published: 2003-04-15

Abstract
Catadioptric sensors are visual sensors that employ lenses (dioptrics) and mirrors (catoptrics). We present a general method of catadioptric sensor design for realizing prescribed projections. Our method makes use of geometric distributions in. 3-dimensional space, which are generalizations of vector fields. The main idea is this: if one desires a reflective surface that will image the world in a certain way, then this condition determines the orientation of the tangent planes to the surface. Analytically, this means that the surface will then be determined by a pair of partial differential equations, which may or may not have a common solution. We show how to check if a common solution exists. If no common solution exists, we describe a method for obtaining optimal approximate solutions in a least-squares sense. As an example application, we construct a mirror that will give a panoramic view of a scene without any digital unwarping.

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