Share Email Print

Proceedings Paper

Energy functions for regularization algorithms
Author(s): Herve Delingette; Martial Hebert; Katsushi Ikeuchi
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Energy functions used for regularization algorithms measure the smoothness of a curve or surface. In order, to render acceptable solutions, these energies have to verify certain properties such as invariance with Euclidean transformations or invariance with parametrization. This paper extends the notion of smoothness energy to the notion of differential stabilizer. If an analogy is made with mechanics, smoothness energy corresponds to potential energy while differential stabilizers correspond to forces. To avoid the systematic underestimation of curvature for planar curve fitting, it is necessary that circles be the curves of maximum smoothness. Finally a set of stabilizers is proposed that meets this condition as well as invariance with rotation and parametrization.

Paper Details

Date Published: 1 September 1991
PDF: 12 pages
Proc. SPIE 1570, Geometric Methods in Computer Vision, (1 September 1991); doi: 10.1117/12.49979
Show Author Affiliations
Herve Delingette, Carnegie Mellon Univ. (United States)
Martial Hebert, Carnegie Mellon Univ. (United States)
Katsushi Ikeuchi, Carnegie Mellon Univ. (United States)

Published in SPIE Proceedings Vol. 1570:
Geometric Methods in Computer Vision
Baba C. Vemuri, Editor(s)

© SPIE. Terms of Use
Back to Top