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Automatic Projector Calibration Using Self-Identifying Patterns

Authors: Mark Fiala;

Automatic Projector Calibration Using Self-Identifying Patterns

Abstract

Calibrating multiple monitor or projector display elements to provide a composite image can be a time-consuming task if performed manually. Ideally the user would like to roughly aim a number of projectors at a surface, define the desired display corners, and have some automatic method to align the display. A digital camera and computer vision can be used to calibrate the projectors with the assistance of self-identifying patterns. To account for distortion effects and to equalize brightness, it is desirable to know the mapping of many points within each projector image. A small set of images can be projected from each display element if a self-identifying pattern is used. An array of ARTag markers are used as a self-identifying pattern which is displayed in turn by each of the display monitors or projectors and recognized in the camera image. In this way an ad-hoc arrangement of projectors can be calibrated in seconds. Experimental results are shown validating this architecture.

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Powered by OpenAIRE graph
Found an issue? Give us feedback
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!
16
Average
Top 10%
Top 10%
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