CloudAR：一个基于云的移动增强现实框架
CloudAR: A Cloud-based Framework for Mobile Augmented Reality
摘要：
最近的移动设备的计算能力实现了用于增强现实（AR）的自然特征处理。然而，移动AR应用仍然面临着可扩展性和性能挑战。在本文中，我们提出了CloudAR，这是一个移动AR框架，通过识别任务卸载利用云和边缘计算的优势。我们详尽地探索了基于云的AR的设计空间，并优化了卸载管道，以最大限度地减少时间和能源消耗。我们为移动设备设计了一个创新的跟踪系统，它提供了6自由度（6DoF）的轻量级跟踪，并隐藏了用户感知的卸载延迟。我们还设计了一个多对象图像检索管道，在服务器上执行快速准确的图像识别任务。在我们的测试中，使用CloudAR框架构建的移动AR应用平均每秒运行30帧（FPS），精确跟踪只有1~2个像素的错误，图像识别的准确率至少为97%。我们的研究结果还表明，CloudAR在几个性能指标上优于领先的商业AR框架之一。
英文摘要：
Computation capabilities of recent mobile devices enable natural feature processing for Augmented Reality (AR). However, mobile AR applications are still faced with scalability and performance challenges. In this paper, we propose CloudAR, a mobile AR framework utilizing the advantages of cloud and edge computing through recognition task offloading. We explore the design space of cloud-based AR exhaustively and optimize the offloading pipeline to minimize the time and energy consumption. We design an innovative tracking system for mobile devices which provides lightweight tracking in 6 degree of freedom (6DoF) and hides the offloading latency from users' perception. We also design a multi-object image retrieval pipeline that executes fast and accurate image recognition tasks on servers. In our evaluations, the mobile AR application built with the CloudAR framework runs at 30 frames per second (FPS) on average with precise tracking of only 1~2 pixel errors and image recognition of at least 97% accuracy. Our results also show that CloudAR outperforms one of the leading commercial AR framework in several performance metrics.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
