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Multiscale-VR: Multiscale Gigapixel 3D Panoramic Videography for Virtual Reality

机译:Multiscale-VR:用于虚拟现实的多尺度千兆像素3D全景摄影

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Creating virtual reality (VR) content with effective imaging systems has attracted significant attention worldwide following the broad applications of VR in various fields, including entertainment, surveillance, sports, etc. However, due to the inherent trade-off between field-of-view and resolution of the imaging system as well as the prohibitive computational cost, live capturing and generating multiscale 360° 3D video content at an eye-limited resolution to provide immersive VR experiences confront significant challenges. In this work, we propose Multiscale-VR, a multiscale unstructured camera array computational imaging system for high-quality gigapixel 3D panoramic videography that creates the six-degree-of-freedom multiscale interactive VR content. The Multiscale-VR imaging system comprises scalable cylindrical-distributed global and local cameras, where global stereo cameras are stitched to cover 360° field-of-view, and unstructured local monocular cameras are adapted to the global camera for flexible high-resolution video streaming arrangement. We demonstrate that a high-quality gigapixel depth video can be faithfully reconstructed by our deep neural network-based algorithm pipeline where the global depth via stereo matching and the local depth via high-resolution RGB-guided refinement are associated. To generate the immersive 3D VR content, we present a three-layer rendering framework that includes an original layer for scene rendering, a diffusion layer for handling occlusion regions, and a dynamic layer for efficient dynamic foreground rendering. Our multiscale reconstruction architecture enables the proposed prototype system for rendering highly effective 3D, 360° gigapixel live VR video at 30 fps from the captured high-throughput multiscale video sequences. The proposed multiscale interactive VR content generation approach by using a heterogeneous camera system design, in contrast to the existing single-scale VR imaging systems with structured homogeneous cameras, will open up new avenues of research in VR and provide an unprecedented immersive experience benefiting various novel applications.
机译:随着VR在娱乐,监视,体育等各个领域的广泛应用,使用有效的成像系统创建虚拟现实(VR)内容已引起全世界的广泛关注。但是,由于视场之间固有的权衡关系成像系统的分辨率和令人望而却步的计算成本,实时捕捉并以有限的分辨率生成多尺度360°3D视频内容以提供身临其境的VR体验面临着巨大的挑战。在这项工作中,我们提出了Multiscale-VR,这是一种用于创建六自由度多尺度交互式VR内容的高质量千兆像素3D全景摄影的多尺度非结构化相机阵列计算成像系统。 Multiscale-VR成像系统包括可伸缩的圆柱形分布式全局和局部摄像机,其中全局立体摄像机被缝合以覆盖360°视野,非结构化的局部单目摄像机适用于全局摄像机,以实现灵活的高分辨率视频流安排。我们证明了可以通过我们基于深度神经网络的算法流水线忠实地重建高质量的千兆像素深度视频,该流水线将通过立体匹配的全局深度和通过高分辨率RGB引导的精细化的局部深度关联在一起。为了生成沉浸式3D VR内容,我们提出了一个三层渲染框架,其中包括用于场景渲染的原始层,用于处理遮挡区域的扩散层以及用于有效的动态前景渲染的动态层。我们的多尺度重建体系结构使拟议的原型系统能够从捕获的高通量多尺度视频序列中以30 fps渲染高效的3D,360°千兆像素实时VR视频。与现有的具有结构化同质相机的单比例VR成像系统相比,所提出的采用异构相机系统设计的多比例交互式VR内容生成方法将为VR开辟新的研究途径,并提供前所未有的身临其境的体验,从而有益于各种小说应用程序。

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