竞技场的回声:走向体育赛事的3D直播

IF 7.8 1区 计算机科学 Q1 COMPUTER SCIENCE, SOFTWARE ENGINEERING
Junkai Huang, Saswat Subhajyoti Mallick, Alejandro Amat, Marc Ruiz Olle, Albert Mosella-Montoro, Bernhard Kerbl, Francisco Vicente Carrasco, Fernando De la Torre
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引用次数: 0

摘要

以人为中心的现场活动在塑造文化和促进社会联系方面一直发挥着关键作用。传统的2D直播无法复制现场观众身临其境的体验。为了解决这一问题,本文提出了LiveSplats,这是一个使用高性能三维高斯飞溅对现场事件进行实时、逼真的3D重建的框架。我们的解决方案利用强大的几何先验,通过分布式处理和负载平衡进行优化,实现交互式、自由探索的3D体验。通过将场景重建分为以演员为中心和特定于环境的任务,我们采用分层的粗到精优化,基于姿态数据快速准确地重建人类演员,并通过光度损失来细化他们的几何形状和外观。对于静态环境,我们专注于依赖于视图的外观变化,简化渲染效率并最大化GPU性能。为了便于评估,我们引入(并分发)一个篮球比赛的合成基准数据集,提供高视觉保真度作为基础事实。在我们的合成基准测试和公开可用的基准测试中,LiveSplats始终优于现有的方法。该数据集可在https://humansensinglab.github.io/basket-multiview上获得。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Echoes of the Coliseum: Towards 3D Live streaming of Sports Events
Human-centered live events have always played a pivotal role in shaping culture and fostering social connections. Traditional 2D live transmissions fail to replicate the immersive quality of physical attendance. Addressing this gap, this paper proposes LiveSplats , a framework towards real-time, photo-realistic 3D reconstructions of live events using high-performance 3D Gaussian Splatting. Our solution capitalizes on strong geometric priors to optimize through distributed processing and load balancing, enabling interactive, freely explorable 3D experiences. By dividing scene reconstruction into actor-centric and environment-specific tasks, we employ hierarchical coarse-to-fine optimization to rapidly and accurately reconstruct human actors based on pose data, refining their geometry and appearance with photometric loss. For static environments, we focus on view-dependent appearance changes, streamlining rendering efficiency and maximizing GPU performance. To facilitate evaluation, we introduce (and distribute) a synthetic benchmark dataset of basketball games, offering high visual fidelity as ground truth. In both our synthetic benchmark and publicly available benchmarks, LiveSplats consistently outperforms existing approaches. The dataset is available at https://humansensinglab.github.io/basket-multiview.
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来源期刊
ACM Transactions on Graphics
ACM Transactions on Graphics 工程技术-计算机:软件工程
CiteScore
14.30
自引率
25.80%
发文量
193
审稿时长
12 months
期刊介绍: ACM Transactions on Graphics (TOG) is a peer-reviewed scientific journal that aims to disseminate the latest findings of note in the field of computer graphics. It has been published since 1982 by the Association for Computing Machinery. Starting in 2003, all papers accepted for presentation at the annual SIGGRAPH conference are printed in a special summer issue of the journal.
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