Name
Abstract | ||
|---|---|---|
•A new method to fit parabolic curves is presented.•The method is fast and robust to noisy observations due to the use of absolute error minimization.•Stability is further improved by normalization of the directrix vector.•Our approach outperforms state of the art competitors in both synthetic and real datasets. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.patcog.2018.07.019 | Pattern Recognition |
Keywords | Field | DocType |
Parabolic fitting,Geometric curve fitting,Noise,Minimization of absolute errors,Robust estimation | Standard curve,Square (algebra),Normalization (statistics),Pattern recognition,Minification,Artificial intelligence,Mathematics,Parabola | Journal |
Volume | Issue | ISSN |
84 | 1 | 0031-3203 |
Citations | PageRank | References |
0 | 0.34 | 25 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ezequiel López-Rubio | 1 | 21 | 5.48 |
| Karl Thurnhofer-Hemsi | 2 | 3 | 6.11 |
| E. B. Blázquez-Parra | 3 | 1 | 1.36 |
| O. D. Cózar-Macías | 4 | 0 | 1.35 |
| M. Carmen Ladrón-de-Guevara-Muñoz | 5 | 0 | 0.34 |