Name
Abstract | ||
|---|---|---|
This paper deals with a recently proposed non- parametric approach to camera calibration, which is ap- plicable to any type of sensor design. Currently, no relative quantitative performance data is available for this method. This paper addresses this issue, by providing a comprehen- sive evaluation with respect to the standard planar calibra- tion technique in the literature. Experiments are conducted on simulated and real data, with thefirm conclusion that the generic calibration method has the capability to outperform the standard parametric approach for imaging systems with significant distortion. The results provide important practi- cal information for the vision community at large. |
Year | Venue | Keywords |
|---|---|---|
2007 | MVA | detectors,machine vision,camera calibration,image processing |
Field | DocType | Citations |
Computer vision,Computer science,Camera auto-calibration,Nonparametric statistics,Camera resectioning,Parametric statistics,Planar,Artificial intelligence,Detector,Distortion,Calibration | Conference | 6 |
PageRank | References | Authors |
0.46 | 13 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Aubrey K. Dunne | 1 | 15 | 0.97 |
| John Mallon | 2 | 97 | 7.88 |
| Paul F. Whelan | 3 | 561 | 39.95 |