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Active Rearranged Capturing of Image-Based Rendering Scenes—Theory and Practice

机译:基于图像的渲染场景的主动重排捕获—理论与实践

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摘要

In this paper, we propose to capture image-based rendering scenes using a novel approach called active rearranged capturing (ARC). Given the total number of available cameras, ARC moves them strategically on the camera plane in order to minimize the sum of squared rendering errors for a given set of light rays to be rendered. Assuming the scene changes slowly so that the optimized camera locations are valid in the next time instance, we formulate the problem as a recursive weighted vector quantization problem, which can be solved efficiently. The ARC approach is verified on both synthetic and real-world scenes. In particular, a large self-reconfigurable camera array is built to demonstrate ARC's performance on real-world scenes. The system renders virtual views at 5-10 frames/s depending on the scene complexity on a moderately equipped computer. Given the virtual view point, the cameras move on a set of rails to perform ARC and improve the rendering quality on the fly
机译:在本文中,我们建议使用一种称为主动重排捕获(ARC)的新颖方法来捕获基于图像的渲染场景。给定可用摄像机的总数,ARC会在摄像机平面上策略性地移动它们,以最大程度减少要渲染给定光线集的渲染误差平方和。假设场景变化缓慢,以使优化的摄像机位置在下一次实例中有效,我们将该问题公式化为递归加权矢量量化问题,可以有效解决该问题。 ARC方法已在合成和真实场景中得到验证。特别是,构建了一个大型的可自我重新配置的摄像机阵列,以演示ARC在现实场景中的性能。该系统根据装备适当的计算机上的场景复杂性,以5-10帧/秒的速度渲染虚拟视图。给定虚拟视点,摄像机在一组导轨上移动以执行ARC并实时提高渲染质量

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