Cultural advice

The Australian National University acknowledges, celebrates and pays our respects to the Ngunnawal and Ngambri people of the Canberra region and to all First Nations Australians on whose traditional lands we meet and work, and whose cultures are among the oldest continuing cultures in human history.

Aboriginal and Torres Strait Islander peoples are advised that ANU Library collections may include images, names, voices, and other representations of deceased persons.

Material in the collection may contain terms, language or views that reflect the period in which the item was created and may be considered inappropriate today.

Iterative Extensions of the Sturm/Triggs Algorithm: Convergence and Nonconvergence

Loading...
Thumbnail Image

Date

Authors

Oliensis, John
Hartley, Richard

Journal Title

Journal ISSN

Volume Title

Publisher

Springer

Abstract

We show that SIESTA, the simplest iterative extension of the Sturm/Triggs algorithm, descends an error function. However, we prove that SIESTA does not converge to usable results. The iterative extension of Mahamud et al. has similar problems, and experiments with "balanced" iterations show that they can fail to converge. We present CIESTA, an algorithm which avoids these problems. It is identical to SIESTA except for one extra, simple stage of computation. We prove that CIESTA descends an error and approaches fixed points. Under weak assumptions, it converges. The CIESTA error can be minimized using a standard descent method such as Gauss-Newton, combining quadratic convergence with the advantage of minimizing in the projective depths.

Description

Citation

Source

Proceedings of the 9th European Conference part IV (ECCV 2006)

Book Title

Entity type

Access Statement

License Rights

Restricted until

2037-12-31