Automatic projector calibration with embedded light sensors

Authors:
Johnny C. Lee;Paul H. Dietz;Dan Maynes-Aminzade;Ramesh Raskar;Scott E. Hudson
Affiliations:
Carnegie Mellon University, Pittsburgh, PA and Mitsubishi Electric Research Laboratories, Cambridge, MA;Mitsubishi Electric Research Laboratories, Cambridge, MA;Mitsubishi Electric Research Laboratories, Cambridge, MA and Stanford University, Stanford, CA;Mitsubishi Electric Research Laboratories, Cambridge, MA;Carnegie Mellon University, Pittsburgh, PA
Venue:
Proceedings of the 17th annual ACM symposium on User interface software and technology
Year:
2004

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Abstract

Projection technology typically places several constraints on the geometric relationship between the projector and the projection surface to obtain an undistorted, properly sized image. In this paper we describe a simple, robust, fast, and low-cost method for automatic projector calibration that eliminates many of these constraints. We embed light sensors in the target surface, project Gray-coded binary patterns to discover the sensor locations, and then prewarp the image to accurately fit the physical features of the projection surface. This technique can be expanded to automatically stitch multiple projectors, calibrate onto non-planar surfaces for object decoration, and provide a method for simple geometry acquisition.