To provide an image processing system and the like which can correct image distortions and provide properly overlapped images when a plurality of projectors are used to project overlapped images, a projector includes: an image projection section projecting an image based on image signals to display the image in a manner to overlap another image projected from another projector at a projection target area; sensing section sensing an image and generating sensing information; overlap-area detecting section detecting projection areas for the projection target area, and detecting an overlap area at which the projection areas overlap, based on the sensing information; correction information generating section generating correction information indicating information for positions of the projection areas and a position of the overlap area; and projection area correction section correcting image signals, based on the correction information, to project an image onto a region corresponding to the overlap area.

Image processing system, projector, program, information storage medium and image processing method

Projectors are currently undergoing a transformation as they evolve from static output devices to portable, environment-aware, communicating systems. An enhanced projector can determine and respond to the geometry of the display surface, and can be used in an ad-hoc cluster to create a self-configuring display. Information display is such a prevailing part of everyday life that new and more flexible ways to present data are likely to have significant impact. This paper examines geometrical issues for enhanced projectors, relating to customized projection for different shapes of display surface, object augmentation, and co-operation between multiple units.We introduce a new technique for adaptive projection on non-planar surfaces using conformal texture mapping. We describe object augmentation with a hand-held projector, including interaction techniques. We describe the concept of a display created by an ad-hoc cluster of heterogeneous enhanced projectors, with a new global alignment scheme, and new parametric image transfer methods for quadric surfaces, to make a seamless projection. The work is illustrated by several prototypes and applications.

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iLamps: geometrically aware and self-configuring projectors

Multiprojector, large-scale displays are used in scientific visualization, virtual reality, and other visually intensive applications. In recent years, a number of camera-based computer vision techniques have been proposed to register the geometry and color of tiled projection-based display. These automated techniques use cameras to "calibrate" display geometry and photometry, computing per-projector corrective warps and intensity corrections that are necessary to produce seamless imagery across projector mosaics. These techniques replace the traditional labor-intensive manual alignment and maintenance steps, making such displays cost-effective, flexible, and accessible. In this paper, we present a survey of different camera-based geometric and photometric registration techniques reported in the literature to date. We discuss several techniques that have been proposed and demonstrated, each addressing particular display configurations and modes of operation. We overview each of these approaches and discuss their advantages and disadvantages. We examine techniques that address registration on both planar (video walls) and arbitrary display surfaces and photometric correction for different kinds of display surfaces. We conclude with a discussion of the remaining challenges and research opportunities for multiprojector displays

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Camera-based calibration techniques for seamless multiprojector displays

A method is described that involves identifying one or more images of respective one or more fixed markers. Each marker is positioned on or proximate to a display. The images appear on a pixilated sensor within a handheld device. The method also involves determining a location on, or proximate to, the display where the handheld device was pointed during the identifying. The method also involves sending from the handheld device information derived from the identifying of the one or more images of respective one or more fixed markers. The method also involves triggering action taken by electronic equipment circuitry in response to the handheld device's sending of a signal to indicate the action is desired.

Handheld vision based absolute pointing system

In this paper, we describe a novel camera calibration method to estimate the extrinsic parameters and the focal length of a camera by using only one single image of two coplanar circles with arbitrary radius.

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Camera Calibration with Two Arbitrary Coplanar Circles

Standard presentation systems consisting of a laptop connected to a projector suffer from two problems: (1) the projected image appears distorted (keystoned) unless the projector is precisely aligned to the projection screen; (2) the speaker is forced to interact with the computer rather than the audience. This paper shows how the addition of an uncalibrated camera, aimed at the screen, solves both problems. Although the locations, orientations and optical parameters of the camera and projector are unknown, the projector-camera system calibrates itself by exploiting the homography between the projected slide and the camera image. Significant improvements are possible over passively calibrating systems since the projector actively manipulates the environment by placing feature points into the scene. For instance, using a low-resolution (160/spl times/120) camera, we can achieve an accuracy of /spl plusmn/3 pixels in a 1024/spl times/768 presentation slide. The camera-projector system infers models for the projector-to-camera and projector-to-screen mappings in order to provide two major benefits.

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Smarter presentations: exploiting homography in camera-projector systems

Projection systems have become the ubiquitous infrastructure for presentation technology. However, unless the projector is precisely aligned to the presentation screen, the resulting image suffers from perspective (keystone) distortions requiring manual optical or digital correction. This tedious process must be repeated whenever the projector or screen is moved and is increasingly relevant given the emerging trend towards highly-portable LCD projection systems. This paper presents a presentation interface that pre-warps the image to be projected in such a way that the distortions induced by the projector-screen geometry precisely negate the warping. An uncalibrated, low-resolution digital camera is used to infer the projector-screen geometry and to automatically determine the pre-warping parameters. This vision-based system is augmented with a natural interface that enables the user to interactively refine the suggested rectification. Arbitrary distortions due to projector placement are negated, allowing the projector (and camera) to be placed anywhere in the presentation room -- for instance, at the side rather than the center of the room. Our solution works with existing projector hardware, and could easily be incorporated into the next generation of LCD projector systems.

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Matthew D. Mullin

Papers

Smarter presentations: exploiting homography in camera-projector systems

AutomaticKeystone Correction for Camera-Assisted Presentation Interfaces