Autocalibration with the Minimum Number of Cameras with Known Pixel Shape
We address the problem of the Euclidean upgrading of a projective calibration of a minimal set of cameras with known pixel shape and otherwise arbitrarily varying intrinsic and extrinsic parameters. To this purpose, we introduce as our basic geometric tool the six-line conic variety (SLCV), consisti...
| Autores: | , , |
|---|---|
| Tipo de recurso: | artículo |
| Fecha de publicación: | 2011 |
| País: | España |
| Institución: | Universidad Complutense de Madrid (UCM) |
| Repositorio: | Docta Complutense |
| Idioma: | inglés |
| OAI Identifier: | oai:docta.ucm.es:20.500.14352/42061 |
| Acceso en línea: | https://hdl.handle.net/20.500.14352/42061 |
| Access Level: | acceso abierto |
| Palabra clave: | Camera autocalibration Varying parameters Square pixels Three-dimensional reconstruction Absolute Conic Six Line Conic Variety Inteligencia artificial (Informática) 1203.04 Inteligencia Artificial |
| Sumario: | We address the problem of the Euclidean upgrading of a projective calibration of a minimal set of cameras with known pixel shape and otherwise arbitrarily varying intrinsic and extrinsic parameters. To this purpose, we introduce as our basic geometric tool the six-line conic variety (SLCV), consisting in the set of planes intersecting six given lines of 3D space in points of a conic. We show that the set of solutions of the Euclidean upgrading problem for three cameras with known pixel shape can be parameterized in a computationally efficient. As a consequence, we propose an algorithm that performs a Euclidean upgrading with 5 ({theoretical minimum}) or more cameras with the knowledge of the pixel shape as the only constraint. We provide experiments with real images showing the good performance of the technique. |
|---|