Collaborative Research: CNS Core: Small: From Capture to Consumption: System Challenges in Pervasive 360-Degree Video Sharing

360度视频允许用户从相机位置以任何角度探索记录的场景。360度视频格式提供的这种更大的灵活性使其越来越受欢迎。然而，由于这种格式需要大量资源，广泛采用的速度有所放缓。该工作提出了在360度视频共享路径的每个阶段，从发送方的视频捕获到接收方的消费，提高效率的方法。该项目通过四项研究努力应对这些挑战。第一个推力探索了在使用商用镜头捕获的多个视频的实时拼接过程中生成高质量帧的方法。该方法使用梯度下降来细化初始的粗拼接。第二个重点是研究基于可用带宽在空间上调整要上传的内容的机制。第三个推力旨在优化全方位内容的细粒度表示，以实现高投影效率和查看效率。最后一个推力使用边缘计算技术来优化接收方的前瞻窗口大小，以实现带宽高效的内容下载。在项目过程中开发的技术将使用户能够享受更高效的360度视频流应用。这些技术不仅适用于360度视频流媒体，还将在未来几代虚拟现实(VR)技术中应用。该项目还将激发学生对计算机科学研究的普遍兴趣，在项目研究过程中直接培训学生，并为课程开发做出贡献。该项目将产生出版物、代码、数据和其他研究成果。在项目过程中，所有这些构件都将通过URL http://www.cs.gmu.edu/~sqchen/和http://www.cs.binghamton.edu/~yaoliu/公开提供，并在项目完成后至少五年内保持可用。该代码将是开源的，也将在代码托管网站(如GitHub)上提供。该奖项反映了NSF的法定使命，并已通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

360-degree video allows users to explore a recorded scene at any angle from the camera position. This greater flexibility provided by the 360-degree video format has led to its increased popularity. However, widespread adoption has slowed because of the large amounts of resources required by the format. This work proposes methods to improve efficiency at each stage of the 360-degree video sharing path, from video capture at the sender side to consumption at the receiver side. The project addresses these challenges via four research thrusts. The first thrust explores approaches for generating high-quality frames during real-time stitching of multiple videos captured using commodity lenses. The proposed approach applies gradient decent to refine an initial rough stitching. The second thrust investigates mechanisms to spatially adapt content to be uploaded based on the available bandwidth. The third thrust aims to optimize the fine-grained representation of omnidirectional content to achieve high projection efficiency and view efficiency. The last thrust uses edge computing techniques to optimize the look-ahead window size on the receiver side to allow bandwidth-efficient content downloading.The techniques developed during the course of the project will allow users to enjoy more efficient 360-degree video streaming applications. These techniques are not only applicable to 360-degree video streaming but will also have applications in future generations of virtual reality (VR) technologies. The project will also motivate general student interest in computer science research, directly train students during the course of the project’s research, and contribute to curriculum development. The project will produce publications, code, data, and other research artifacts. All such artifacts will be made available publicly through the URLs http://www.cs.gmu.edu/~sqchen/ and http://www.cs.binghamton.edu/~yaoliu/ during the course of the project and remain available for at least five years after completion of the project. The code will be open sourced and will also be made available at code hosting website, e.g., GitHub.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.