| Title | Exploiting p-Fold Symmetries for Faster Polynomial Equation Solving |
| Authors | Erik Ask, Yubin Kuang, Karl Åström |
| Full-text | Available as PDF, Restricted Access |
| Publication | 21st International Conference on Pattern Recognition (ICPR 2012), Proceedings of |
| Year | 2012 |
| Pages | 3232 - 3235 |
| Document type | Conference paper |
| Conference name | 21st International Conference on Pattern Recognition (ICPR 2012) |
| Conference Date | 2012-11-11/2012-11-15 |
| Conference Location | Tsukuba, Japan |
| Status | Published |
| Quality controlled | Yes |
| Language | eng |
| Publisher | International Association for Pattern Recognition (IAPR) & IEEE |
| Abstract English | Numerous geometric problems in computer vision in-<br> volve the solution of systems of polynomial equations.<br> This is true for problems with minimal information, but<br> also for finding stationary points for overdetermined<br> problems. The state-of-the-art is based on the use of<br> numerical linear algebra on the large but sparse co-<br> efficient matrix that represents the expanded original<br> equation set. In this paper we present two simplifica-<br> tions that can be used (i) if the zero vector is one of<br> the solutions or (ii) if the equations display certain p-<br> fold symmetries. We evaluate the simplifications on a<br> few example problems and demonstrate that significant<br> speed increases are possible without loosing accuracy. |
| Keywords | geometry, algebra, computer vision, Polynomial equation solving, |
| ISBN/ISSN/Other | ISBN: 978-4-9906441-1-6 |
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