多尺度vr:用于虚拟现实的多尺度千兆像素3D全景摄像

Jianing Zhang, Tianyi Zhu, Anke Zhang, Xiaoyun Yuan, Zihan Wang, Sebastian Beetschen, Lan Xu, Xing Lin, Qionghai Dai, Lu Fang
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引用次数: 14

摘要

随着VR在娱乐、监控、体育等各个领域的广泛应用,利用有效的成像系统创建虚拟现实(VR)内容引起了全世界的广泛关注。然而,由于成像系统的视场和分辨率之间的内在权衡以及令人望而却步的计算成本,在人眼有限的分辨率下实时捕获和生成多尺度360°3D视频内容以提供沉浸式VR体验面临着重大挑战。在这项工作中,我们提出了多尺度非结构化相机阵列计算成像系统multiscale -VR,用于高质量的千兆像素3D全景摄像,创建六自由度多尺度交互式VR内容。多尺度vr成像系统包括可扩展的圆柱形分布全局和局部摄像机,其中全局立体摄像机缝合以覆盖360°视场,非结构化局部单目摄像机适应全局摄像机,以实现灵活的高分辨率视频流安排。我们证明了高质量的十亿像素深度视频可以通过基于深度神经网络的算法管道忠实地重建,其中通过立体匹配的全局深度和通过高分辨率rgb引导的细化的局部深度相关联。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和用于高效动态前景渲染的动态层。我们的多尺度重建架构使所提出的原型系统能够从捕获的高吞吐量多尺度视频序列中以30 fps的速度渲染高效的3D, 360°十亿像素实时VR视频。采用异构相机系统设计的多尺度交互式VR内容生成方法,与现有的采用结构化同质相机的单尺度VR成像系统形成对比,将为VR研究开辟新的途径,并提供前所未有的沉浸式体验,有利于各种新颖的应用。
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Multiscale-VR: Multiscale Gigapixel 3D Panoramic Videography for Virtual Reality
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.
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Awards [3 award winners] NLDNet++: A Physics Based Single Image Dehazing Network Action Recognition from a Single Coded Image Fast confocal microscopy imaging based on deep learning Comparing Vision-based to Sonar-based 3D Reconstruction
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