Absolute rotation estimation including outlier detection via low-rank and sparse matrix decomposition
US9846974B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 5, 2014 |
| Grant date | Dec 19, 2017 |
| Priority date | — |
| Expiry date | Feb 6, 2036 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2219/2016
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The present disclosure is directed to systems and methods to perform absolute rotation estimation including outlier detection via low-rank and sparse matrix decomposition. One example method includes obtaining a relative rotation estimates matrix that includes a plurality of relative rotation estimates. The method includes determining values for a low-rank matrix that result in a desirable value of a cost function that is based on a low-rank and sparse matrix decomposition of the relative rotation estimates matrix. The cost function includes the low-rank matrix and a sparse matrix that is nonzero in correspondence of one or more outliers of the plurality of relative rotation estimates. The method includes determining an absolute rotations matrix that includes a plurality of absolute rotations based at least in part on the values of the low-rank matrix that result in the desirable value of the cost function.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.