A simplified concentric mosaics system with non-uniformly distributed pre-captured images

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In this paper, a simplified implementation of the Concentric Mosaics image-based rendering technique is proposed. The greatest difficulty for an ordinary user in obtaining the pre-captured images for use in the Concentric Mosaics technique is the precise control of the rotation of a long beam. In the proposed Simplified Concentric Mosaics technique, the camera positions where the pre-captured images will be taken are not precisely controlled, but are estimated from the pre-captured images. We use a stereo technique for estimation of camera positions in this special scenario instead of using the traditional camera pose estimation methods of computer vision. The estimation errors have been analyzed and a closed-loop constraint is used to achieve better rotation angle estimation. In addition, a ratio fitting technique is proposed to select good matching features in the special triview matching detection scenario, which subsequently improves rotation angle estimation. Another contribution of the paper is a pre-processing step to eliminate or reduce the possible vertical offsets and other distortions in the pre-captured images, which are caused by any possible motions of the camera that deviate from the ideal one. In a column-based view synthesis technique like the proposed method and the conventional Concentric Mosaics technique, these vertical offsets and distortions in the pre-captured images will lower the quality of the synthesized images. Thus our pre-processing can be applied on both the proposed method and the ordinary Concentric Mosaics technique. The pre-captured image data structures of both Concentric Mosaics and the proposed method have been illustrated and the comparison has been made. The proposed technique has a similar data structure and thus a similar rendering algorithm as the conventional Concentric Mosaics technique. As a result, it meets our objective that an ordinary user can obtain the Concentric Mosaics type image data and plug it into a common Concentric Mosaics rendering framework. Simulation results show that the proposed method can achieve good rendering results.