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Proceedings Paper

Shape reconstruction from brightness functions
Author(s): Richard J. Gardner; Peyman Milanfar
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Paper Abstract

In this paper we address the problem of reconstructing the shape of a convex object from measurements of the area of its shadows in several directions. This type of very weak measurement is sometime referred to as the brightness function of the object, and may be observed in an imaging scenario by recording the total number of pixels where the object's image appears. These types of measurements, collected as a function of viewing angle, are also referred to as lightcurves in the astrophysics community, and are employed in estimating the shape of atmosphere less rotating bodies (e.g. asteroids). We address the problem of shape reconstruction from brightness functions by constructing a least-squares optimization framework for approximating the underlying shapes with polygons in 2-D, or polyhedra in 3-D, from noisy, and possibly sparse measurements of the brightness values.

Paper Details

Date Published: 20 November 2001
PDF: 12 pages
Proc. SPIE 4474, Advanced Signal Processing Algorithms, Architectures, and Implementations XI, (20 November 2001); doi: 10.1117/12.448654
Show Author Affiliations
Richard J. Gardner, Western Washington Univ. (United States)
Peyman Milanfar, Univ. of California/Santa Cruz (United States)


Published in SPIE Proceedings Vol. 4474:
Advanced Signal Processing Algorithms, Architectures, and Implementations XI
Franklin T. Luk, Editor(s)

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