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A cluster based free viewpoint video system using region-tree based scene reconstruction.

机译：使用基于区域树的场景重构的基于集群的自由视点视频系统。

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摘要

Free viewpoint video (FVV) has been widely speculated as one of the next generation of visual media applications. By taking advantage of camera array based multiple imaging techniques, FVV enables free viewpoint navigation to invoke a sense of "being immersed" for the viewers.;This thesis presents a cluster based FVV system which is designed as a specific application using a new proposed framework for general camera array applications. Our FVV system enables centralized workflow management and distributed computation to take advantage of the cluster's computation power for fast FVV-oriented video processing. For its implementation, effort is mainly focused on the FVV workflow stages of multi-view video acquisition and dense depth based scene reconstruction. Specifically, a new automatic method is proposed for the efficient geometric, photometric and temporal calibrations of a camera array. With this novel integrated calibration method, the use of unsynchronized cameras becomes possible and the multi-view video acquisition is made easy, which greatly facilitate the practical use of a FVV (or camera array based) system. On the other hand, the dense depth based FVV scene reconstruction is addressed as an image discrete labeling problem using a novel coarse-to-fine region-tree based framework. As a general framework, its high ranking evaluations in standard binocular stereo matching and optical flow estimation benchmarking show its effectiveness and versatility. By further extending it for general position multi-view temporal stereo and integrating with inconsistency map/background based progressive optimization, spatial-temporal consistency is enforced in a new and unified way, which greatly helps the final FVV rendering quality. Extensive experimental results show that the new system with its accompanying algorithms can provide high quality rendering results.
机译：自由视点视频（FVV）已被广泛认为是下一代视觉媒体应用程序之一。通过利用基于相机阵列的多种成像技术，FVV使自由视点导航能够为观看者带来一种“沉浸式”的感觉。；本文提出了一种基于集群的FVV系统，该系统使用新提出的框架设计为特定的应用程序适用于一般相机阵列应用。我们的FVV系统支持集中的工作流管理和分布式计算，以利用群集的计算能力来进行面向FVV的快速视频处理。对于其实现，工作主要集中在多视图视频获取和基于密集深度的场景重构的FVV工作流程阶段。具体而言，提出了一种新的自动方法，用于相机阵列的高效几何，光度和时间校准。通过这种新颖的集成校准方法，可以使用不同步的摄像机，并且可以轻松获取多视点视频，这极大地促进了FVV（或基于摄像机阵列）系统的实际使用。另一方面，使用新颖的从粗到细的区域树框架，将基于密集深度的FVV场景重建解决为图像离散标注问题。作为一个通用框架，其在标准双目立体匹配和光流估计基准测试中的高等级评估显示出其有效性和多功能性。通过将其进一步扩展为一般位置的多视图时间立体图像，并与基于不一致的地图/背景的渐进优化集成，可以以一种新的统一方式实施时空一致性，从而极大地提高了最终FVV渲染质量。大量的实验结果表明，新系统及其随附的算法可以提供高质量的渲染结果。

著录项

  • 作者

    Lei, Cheng.;

  • 作者单位

    University of Alberta (Canada).;

  • 授予单位 University of Alberta (Canada).;
  • 学科 Computer Science.
  • 学位 Ph.D.
  • 年度 2009
  • 页码 185 p.
  • 总页数 185
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 老年病学;
  • 关键词

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