2D leapfrog algorithm for optimal surface reconstruction

Lyle Noakes; Ryszard Kozera

doi:10.1117/12.364108

23 September 1999 2D leapfrog algorithm for optimal surface reconstruction

Lyle Noakes, Ryszard Kozera

Proceedings Volume 3811, Vision Geometry VIII; (1999) https://doi.org/10.1117/12.364108
Event: SPIE's International Symposium on Optical Science, Engineering, and Instrumentation, 1999, Denver, CO, United States

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.

Citation Download Citation

Lyle Noakes and Ryszard Kozera "2D leapfrog algorithm for optimal surface reconstruction", Proc. SPIE 3811, Vision Geometry VIII, (23 September 1999); https://doi.org/10.1117/12.364108

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