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We present two families of reflective surfaces that are capable of providing a wide field of view, and yet still approximate a perspective projection to a high degree. These surfaces are derived by considering a plane perpendicular to the axis of a surface of revolution and finding the equations governing the distortion of the image of the plane in this surface. We then view this relation as a differential equation and prescribe the distortion term to be linear. By choosing appropriate initial conditions for the differential equation and solving it numerically, we derive the surface shape and obtain a precise estimate as to what degree the resulting sensor can approximate a perspective projection. Thus these surfaces act as computational sensors, allowing for a wide-angle perspective view of a scene without processing the image in software. The applications of such a sensor should be numerous, including surveillance, robotics and tradition photography.
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Hicks et al. (Thu,) studied this question.
synapsesocial.com/papers/6a204b54284a522d2e2ed2aa — DOI: https://doi.org/10.1109/cvpr.2000.855867
R. Andrew Hicks
Twitter (United States)
Růžena Bajcsy
Nvidia (United Kingdom)
Drexel University
U.S. National Science Foundation
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