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Proceedings Paper

2D leapfrog algorithm for optimal surface reconstruction
Author(s): Lyle Noakes; Ryszard Kozera
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Paper Abstract

In this paper we present an iterative algorithm computing a global optimum for a large system of linear equations enforcing the so-called integrability condition for a given noisy non-integrable vector field. The algorithm will be applied to Photometric Stereo shape reconstruction. The scheme in question (a 2-D Leap-Frog Algorithm) relies neither on a prior knowledge of boundary conditions nor on other global constraints imposed on the so-far derived gradient integration techniques for noise-contaminated data. The proposed algorithm is an improvement of the recently developed Lawn-Mowing Algorithm, which computes a suboptimal solution to the above mentioned problem. The backbone of the proposed algorithm is a generalization of the 1-D Leap-Frog Algorithm derived for finding geodesic joining two points on a Riemannian manifold. The discussion is supplemented by examples illustrating the performance of the 2-D Leap-Frog Algorithm.

Paper Details

Date Published: 23 September 1999
PDF: 12 pages
Proc. SPIE 3811, Vision Geometry VIII, (23 September 1999); doi: 10.1117/12.364108
Show Author Affiliations
Lyle Noakes, Univ. of Western Australia (Australia)
Ryszard Kozera, Univ. of Western Australia (Australia)

Published in SPIE Proceedings Vol. 3811:
Vision Geometry VIII
Longin Jan Latecki; Robert A. Melter; David M. Mount; Angela Y. Wu, Editor(s)

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