CNS Core: Small: Collaborative: Content-Based Viewport Prediction Framework for Live Virtual Reality Streaming
CNS Core: Small: Collaborative: Content-Based Viewport Prediction Framework for Live Virtual Reality Streaming
批准号:
1910085
负责人:
Sheng Wei
金额:
$21.49万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-08-15 至 2022-07-31
中文摘要
随着移动头盔显示器(HMD)设备在消费视频市场的迅速采用,虚拟现实(VR)视频流最近越来越受欢迎。随着沉浸式体验成本的下降,VR视频流带来了新的带宽和性能挑战,尤其是在直播中,因为提供了360度视图。该项目开发了一种新的基于内容的视点预测框架,以提高VR直播的带宽和性能,该框架通过跟踪视频中的运动对象、提取视频语义和对用户感兴趣的视点进行建模的融合来预测用户的视点。首先,通过跟踪对象的运动和语义,开发了一个基于内容的视点预测框架,用于实时VR流媒体。其次,它使用硬件和软件技术来促进实时执行,并将视点预测机制扩展到大量用户。第三,它开发了评估框架来验证该方法的功能、性能和可伸缩性。该项目独特地考虑了视频内容和用户行为之间的相关性,利用前者的确定性性质来克服后者的随机性。随着VR系统在特定领域沉浸式环境中的迅速普及,该项目将受益于几个与VR相关的研究领域,显著节省带宽并提高性能,如基于VR的直播、医疗保健和科学可视化。此外,该项目的跨学科性质将加强对若干科学、技术、工程和数学领域中代表性不足的少数群体的教育和招聘。项目储存库将存储在一个可公开访问的服务器(https://github.com/hwsel).所有项目数据将在资助期结束后保留至少五年。这一奖励反映了NSF的法定使命,并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。
英文摘要
Virtual reality (VR) video streaming has been gaining popularity recently with the rapid adoption of mobile head mounted display (HMD) devices in the consumer video market. As the cost for the immersive experience drops, VR video streaming introduces new bandwidth and performance challenges, especially in live streaming, due to the delivery of 360-degree views. This project develops a new content-based viewport prediction framework to improve the bandwidth and performance in live VR streaming, which predicts the user's viewport through a fusion of tracking the moving objects in the video, extracting the video semantics, and modeling the user's viewport of interest.This project consists of three research thrusts. First, it develops a content-based viewport prediction framework for live VR streaming by tracking the motions and semantics of the objects. Second, it employs hardware and software techniques to facilitate real-time execution and scale the viewport prediction mechanism to a large number of users. Third, it develops evaluation frameworks to verify the functionality, performance, and scalability of the approach. The project uniquely considers the correlation between video content and user behavior, which leverages the deterministic nature of the former to conquer the randomness of the latter.With the rapidly increasing popularity of VR systems in domain-specific immersive environments, the project will benefit several VR-related fields of studies with significant bandwidth savings and performance improvements, such as VR-based live broadcast, healthcare, and scientific visualization. Moreover, the interdisciplinary nature of the project will enhance the education and recruitment of underrepresented minorities in several science, technology, engineering, and mathematics (STEM) fields.The project repository will be stored on a publicly accessible server (https://github.com/hwsel). All the project data will be maintained for at least five years following the end of the grant period.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.
期刊论文(4)
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DOI:
10.1145/3458305.3463378
发表时间:
2021-07
期刊:
Proceedings of the 12th ACM Multimedia Systems Conference
影响因子:
--
作者:
[Xianglong Feng;Weitian Li;Sheng Wei]
通讯作者:
Xianglong Feng;Weitian Li;Sheng Wei
DOI:
10.1145/3534088.3534351
发表时间:
2022-06
期刊:
Proceedings of the 32nd Workshop on Network and Operating Systems Support for Digital Audio and Video
影响因子:
--
作者:
[Ziehen Zhu;Xianglong Feng;Zhongze Tang;Nan Jiang;Tian Guo;Lisong Xu;Sheng Wei]
通讯作者:
Ziehen Zhu;Xianglong Feng;Zhongze Tang;Nan Jiang;Tian Guo;Lisong Xu;Sheng Wei
DOI:
10.1109/tvcg.2021.3067686
发表时间:
2021-04
期刊:
IEEE Transactions on Visualization and Computer Graphics
影响因子:
5.2
作者:
[Xianglong Feng;Zeyang Bao;Sheng Wei]
通讯作者:
Xianglong Feng;Zeyang Bao;Sheng Wei
LiveDeep: Online Viewport Prediction for Live Virtual Reality Streaming Using Lifelong Deep Learning
LiveDeep:使用终身深度学习进行实时虚拟现实流的在线视口预测
DOI:
10.1109/vr46266.2020.00104
发表时间:
2020
期刊:
IEEE Conference on Virtual Reality and 3D User Interfaces (VR
影响因子:
--
作者:
[Feng, Xianglong, Liu, Yao, Wei, Sheng]
通讯作者:
Wei, Sheng
CAREER: Towards the Security of Heterogeneous CPU-FPGA Systems
-
批准号:1750867
-
项目类别:Continuing Grant
-
资助金额:$49.69万
-
财政年份:2018
-
负责人:Sheng Wei
-
依托单位:
CAREER: Towards the Security of Heterogeneous CPU-FPGA Systems
-
批准号:1912593
-
项目类别:Continuing Grant
-
资助金额:$43.66万
-
财政年份:2018
-
负责人:Sheng Wei
-
依托单位:
国内基金
海外基金
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