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Camera auto-calibration with virtual patterns

Authors: Alfredo Gardel Vicente; José Luis Lázaro; Jean-Marc Lavest;

Camera auto-calibration with virtual patterns

Abstract

This paper studies the multi-image calibration of a camera and how to carry it out in an automatic way making use of a projector. To prepare for multi-image calibration, it is necessary to calibrate the camera. Next, calibrate the projector using that camera. Then calibrate any camera with similar focal length to the previous one. The system doesn't need to incorporate any position platform and is completely automatic once it is disposed. It is based on the generation of images of a virtual pattern. This virtually generated pattern is projected on a fixed blackboard or a wall. Different on-line generated virtual patterns are visualized to carry out the auto-calibration. It is simple and can be repeated for a number of cameras that have an appropriate focal length. Also an improved method for focus of expansion using the same ideas is presented to obtain the principal point for a zoom camera.

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Top 10%
Average
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