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Different Points of View: Impact of 3D Point Cloud Reduction on QoE of Rendered Images

机译:不同的观点:3D点云减少对渲染图像QoE的影响

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Modern photogrammetric methods as well as laser measurement systems make it easy to collect large 3D point clouds that sample objects or environments. As the recorded point clouds can be used to render computer-generated images and models, they are of particular interest in the domains of geographical and architectural engineering, as well as for computer graphics (e.g., games or virtual reality). However, point clouds have a huge storage demand, thus, point clouds shall be reduced by removing some of the points. This will inevitably also reduce the Quality of Experience (QoE) of media, which is rendered from the reduced point clouds. In this work, the impact of two different reduction methods on the QoE of rendered images is investigated from two point of views, i.e., based on ratings from both naive crowdworkers as well as point cloud experts.
机译:现代摄影测量方法以及激光测量系统使收集样本或环境样本的大型3D点云变得很容易。由于记录的点云可用于渲染计算机生成的图像和模型,因此它们在地理和建筑工程领域以及计算机图形(例如游戏或虚拟现实)领域特别受关注。但是,点云具有巨大的存储需求,因此,应通过删除一些点来减少点云。这不可避免地还会降低从减少的点云渲染的媒体体验质量(QoE)。在这项工作中,从两种观点来研究两种不同的缩小方法对渲染图像的QoE的影响,即基于幼稚的群众工作者和点云专家的评级。

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