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Generating and streaming immersive sports video content

机译:生成并串流沉浸式体育视频内容

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摘要

Stereoscopic 3D videos have already become popular in movie theaters with most productions being released in this format. More recently, with the availability of commodity Virtual Reality (VR) products, immersive video content is receiving even more interest. A wide spread adoption of immersive devices and displays is hindered by the lack of content that matches the user expectations. Producing immersive videos is far more costly and time-consuming than regular 2D videos, which makes it challenging and thus rarely attempted, especially for live events, such as sports games. In addition, immersive content needs to be adapted for viewing on different displays/devices. To address these challenges, we first propose a new system for 3D video streaming that provides automatic depth adjustments as one of its key features. Our system takes into account both the content and the display type in order to customize 3D videos and optimize the viewing experience. Our stereoscopic video streaming system was implemented, deployed and tested with real users. Results show that between 60% to 70% of the shots can benefit from our system and more than 25% depth enhancement can be achieved. Next, we propose a novel, data-driven method that converts 2D videos to 3D by transferring depth information from a database of similar 3D videos. Our method then reconstructs the depth map while ensuring temporal coherency using a spatio-temporal formulation of Poisson reconstruction. Results show that our method produces high-quality 3D videos that are almost indistinguishable from videos shot by stereo cameras, while achieving up to 20% improvement in the perceived depth compared to the current state-of-the-art method. Furthermore, we extend our work in the direction of VR, and propose using video feeds from regular broadcasting cameras to generate sports VR content. We generate a wide-angle panorama by utilizing the motion of the main camera. We then use various techniques to remove the parallax, align all video feeds, and overlay them on the panorama. Subjective studies show that our generated content provides an immersive experience similar to ground-truth content captured using a 360 camera, with most subjects rating their sense of presence from Good to Excellent.
机译:立体3D视频已经在电影院中流行,大多数作品都以这种格式发行。最近,随着商品虚拟现实(VR)产品的出现,身临其境的视频内容受到了越来越多的关注。缺乏符合用户期望的内容会阻碍沉浸式设备和显示器的广泛采用。制作沉浸式视频比常规的2D视频更昂贵,更耗时,这使其具有挑战性,因此很少尝试,尤其是对于体育比赛等现场活动。另外,身临其境的内容需要被适配以在不同的显示器/设备上观看。为了解决这些挑战,我们首先提出了一种用于3D视频流的新系统,该系统提供自动深度调整作为其主要功能之一。我们的系统同时考虑内容和显示类型,以自定义3D视频并优化观看体验。我们的立体视频流系统已在实际用户中实施,部署和测试。结果表明,有60%至70%的镜头可以受益于我们的系统,并且可以实现超过25%的深度增强。接下来,我们提出一种新颖的数据驱动方法,该方法通过从相似3D视频的数据库中传输深度信息,将2D视频转换为3D。然后,我们的方法使用泊松重建的时空公式在确保时间一致性的同时重建深度图。结果表明,我们的方法产生的高质量3D视频几乎与立体摄像机拍摄的视频没有区别,同时与目前的最新方法相比,其感知深度最多可提高20%。此外,我们将工作范围扩展到VR领域,并建议使用来自常规广播摄像机的视频馈送来生成体育VR内容。我们利用主摄像机的运动生成一个广角全景图。然后,我们使用各种技术来消除视差,对齐所有视频源并将其覆盖在全景图上。主观研究表明,我们生成的内容提供的沉浸式体验类似于使用360相机捕获的真实内容,并且大多数对象将其存在感从“好”转换为“优秀”。

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    Calagari Kiana;

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