Globally Optimal Least Squares Solutions for Quasiconvex 1D Vision Problems

Carl Olsson, Martin Byröd, Fredrik Kahl

Forskningsoutput: Kapitel i bok/rapport/Conference proceedingKonferenspaper i proceedingPeer review

Sammanfattning

Solutions to non-linear least squares problems play an essential role in structure and motion problems in computer vision. The predominant approach for solving these problems is a Newton like scheme which uses the: hessian of the function to iteratively find a, local solution. Although fast, this strategy inevitably leeds to issues with poor local minima, and missed global minima. In this paper rather than trying to develop all algorithm that is guaranteed to always work, we show that it is often possible to verify that a local solution is in fact; also global. We present a simple test that verifies optimality of a solution using only a few linear programs. We show oil both synthetic and real data that for the vast majority of cases we are able to verify optimality. Further more we show even if the above test fails it is still often possible to verify that the local solution is global with high probability.
Originalspråkengelska
Titel på värdpublikationImage Analysis, Proceedings
FörlagSpringer
Sidor686-695
Volym5575
StatusPublished - 2009
Evenemang16th Scandinavian Conference on Image Analysis - Oslo, Norge
Varaktighet: 2009 juni 152009 juni 18

Publikationsserier

Namn
Volym5575
ISSN (tryckt)1611-3349
ISSN (elektroniskt)0302-9743

Konferens

Konferens16th Scandinavian Conference on Image Analysis
Land/TerritoriumNorge
OrtOslo
Period2009/06/152009/06/18

Ämnesklassifikation (UKÄ)

  • Matematik

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