Geometric computation for machine vision
Geometric computation for machine vision
International Journal of Computer Vision - 1998 Marr Prize
Automatic alignment of high-resolution multi-projector display using an un-calibrated camera
Proceedings of the conference on Visualization '00
Multiple view geometry in computer vision
Multiple view geometry in computer vision
Minimal Conditions on Intrinsic Parameters for Euclidean Reconstruction
ACCV '98 Proceedings of the Third Asian Conference on Computer Vision-Volume II
Multiple View Geometry of Projector-Camera Systems from Virtual Mutual Projection
PSIVT '09 Proceedings of the 3rd Pacific Rim Symposium on Advances in Image and Video Technology
Easy Calibration of a Multi-projector Display System
International Journal of Computer Vision
3D reconstruction of specular surfaces using a calibrated projector–camera setup
Machine Vision and Applications
Flexible online calibration for a mobile projector-camera system
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part IV
Projector calibration by "inverse camera calibration"
SCIA'11 Proceedings of the 17th Scandinavian conference on Image analysis
Geometric calibration of a camera-projector 3D imaging system
Proceedings of the 10th International Conference on Virtual Reality Continuum and Its Applications in Industry
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This paper presents a method for calibrating a projector-camera system that consists of multiple projectors (or multiple poses of a single projector), a camera, and a planar screen. We consider the problem of estimating the homography between the screen and the image plane of the camera or the screen-camera homography, in the case where there is no prior knowledge regarding the screen surface that enables the direct computation of the homography. It is assumed that the pose of each projector is unknown while its internal geometry is known. Subsequently, it is shown that the screen-camera homography can be determined from only the images projected by the projectors and then obtained by the camera, up to a transformation with four degrees of freedom. This transformation corresponds to arbitrariness in choosing a two-dimensional coordinate system on the screen surface and when this coordinate system is chosen in some manner, the screen-camera homography as well as the unknown poses of the projectors can be uniquely determined. A noniterative algorithm is presented, which computes the homography from three or more images. Several experimental results on synthetic as well as real images are shown to demonstrate the effectiveness of the method.