Projector-camera systems drive applications in many fields such as measurement and spatial augmented reality. When needed, we can find their internal and external parameters via geometric calibration. For this process, we have to use both a printed pattern and a projector pattern, but they can easily interfere with each other. Current methods compensate by decoupling their calibrations or by leveraging structured light and color channels, but the required manipulations are not user-friendly. Therefore, we cannot expect normal users to execute the procedure, which can also become a burden for researchers. Although not always required, knowledge of the geometric parameters can often facilitate development of new systems. To make the calibration process easier, we propose a method that uses fiducial markers, from which we can easily derive a prewarp that, once applied to the projector calibration pattern, prevents its interference. Using our method, we confirmed that users can easily calibrate a projector-camera system in less than one minute, which we consider to be user-friendly, while still achieving typical subpixel accuracy.

When an occluding object, such as a person, stands between a projector and a display surface, a shadow results. We can compensate by positioning multiple projectors so they produce identical and overlapping images and by using a system to locate shadows. Existing systems work by detecting either the shadows or the occluders. Shadow detection methods cannot remove shadows before they appear and are sensitive to video projection, while current occluder detection methods require near infrared cameras and illumination. Instead, we propose using a camera-based object tracker to locate the occluder and an algorithm to model the shadows. The algorithm can adapt to other tracking technologies as well. Despite imprecision in the calibration and tracking process, we found that our system performs effective shadow removal with sufficiently low processing delay for interactive applications with video projection.

Projector-camera systems drive applications in many fields such as measurement and spatial augmented reality. When needed, we can find their internal and external parameters via geometric calibration. For this process, we have to use both a printed pattern and a projector pattern, but they can easily interfere with each other. Current methods compensate by decoupling their calibrations or by leveraging structured light and color channels, but the required manipulations are not user-friendly. Therefore, we cannot expect normal users to execute the procedure, which can also become a burden for researchers. Although not always required, knowledge of the geometric parameters can often facilitate development of new systems. To make the calibration process easier, we propose a method that uses fiducial markers, from which we can easily derive a prewarp that, once applied to the projector calibration pattern, prevents its interference. Using our method, we confirmed that users can easily calibrate a projector-camera system in less than one minute, which we consider to be user-friendly, while still achieving typical subpixel accuracy.

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