Existing geometric and radiometric compensation methods for direct-projected augmented reality focus on static projection surfaces rather than dynamic surfaces (with varying geometry in time). We aim at providing an effective framework for projecting a sequence of augmented reality images onto dynamic surfaces without geometric and radiometric distortion. We present our design of a special pattern image for simultaneous geometric and radiometric compensation and evaluate two different techniques for embedding the pattern image into augmented reality images. The validity of the proposed method is examined through a variety of experiments with a mobile projector-camera system.

Many vision tasks such as scene segmentation, or the recognition of materials within a scene, become considerably easier when it is possible to measure the spectral reflectance of scene surfaces. In this paper, we present an efficient and robust approach for recovering spectral reflectance in a scene that combines the advantages of using multiple spectral sources and a multispectral camera. We have implemented a system based on this approach using a cluster of light sources with different spectra to illuminate the scene and a conventional RGB camera to acquire images. Rather than sequentially activating the sources, we have developed a novel technique to determine the optimal multiplexing sequence of spectral sources so as to minimize the number of acquired images. We use our recovered spectral measurements to recover the continuous spectral reflectance for each scene point by using a linear model for spectral reflectance. Our imaging system can produce multispectral videos of scenes at 30fps. We demonstrate the effectiveness of our system through extensive evaluation. As a demonstration, we present the results of applying data recovered by our system to material segmentation and spectral relighting.

In direct-projected augmented reality, use of projector makes it possible to utilize 3-D real and large objects as displays and frees from discomforts incidental to wearing a device such as HMD. However, the resulting augmentation usually has poor depth resolution due to projectors with low contrast. In direct-projected augmented reality, the radiometric compensation, which is originally employed to recover the color properties of the projector input image in direct-projected augmented reality, seems to be another cause of decreasing the final contrast of the augmentation. In this paper, a contrast enhancement method is proposed that combines a hue- and saturation-preserving histogram equalization with the radiometric compensation in direct-projected augmented reality. The method guarantees that the radiometrically compensated color is maintained while the brightness (or intensity) contrast is enhanced. Experimental results demonstrate the validity of our method

In projection-based augmented reality, specular reflection may distract the users. This work demonstrates that the specular reflection can be eliminated by redundantly illuminating the projection surface using multiple overlapping projectors mounted at different locations. Our initial system using two projectors is presented. The system automatically determines the pixels which include specular reflection in one projector, blank the light falling on the pixel and boost the other projector's output so that the added light is projected onto the pixel consistently.