Do We Need Sophisticated System Design for Edge-assisted Augmented Reality?

被引:3
|
作者
Meng, Jiayi [1 ]
Kong, Jonny [1 ]
Hu, Charlie [1 ]
Choi, Mun Gi [2 ]
Lal, Dhananjay [2 ]
机构
[1] Purdue Univ, W Lafayette, IN 47907 USA
[2] Charter Commun, Stamford, CT USA
基金
美国国家科学基金会;
关键词
Edge-assisted Augmented Reality; Deep Neural Network; Object Detection; Video Compression;
D O I
10.1145/3517206.3526267
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
We revisit the performance of a canonical system design for edge-assisted AR that simply combines off-the-shelf H.264 video encoding with a standard object tracking technique. Our experimental analysis shows that the simple canonical design for edge-assisted object detection can achieve within 3.07%/1.51% of the accuracy of ideal offloading (which assumes infinite network bandwidth and the total network transmission time of a single RTT) under LTE/5G mmWave networks. Our findings suggest that recent trend towards sophisticated system architecture design for edge-assisted AR appears unnecessary. We provide insights for why video compression plus on-device object tracking is so effective in edge-assisted object detection, draw implications to edge-assisted AR research, and pose open problems that warrant further investigation into this surprise finding.
引用
收藏
页码:7 / 12
页数:6
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