@techreport{TD:102036,
	att_abstract={{In this paper, we conduct a reality check for mobile Augmented Reality (AR). We dissect and measure the cloud offloading feature for computation-intensive visual tasks of two popular commercial AR systems. Our key finding is that their cloud-based recognition is still not mature and not optimized for latency, data usage and energy consumption. In order to identify the opportunities for further improving the Quality of Experience (QoE) for mobile AR, we break down the end-to-end latency of the pipeline for typical cloud-based mobile AR and pinpoint the dominating components in the critical path.}},
	att_authors={bh1729},
	att_categories={},
	att_copyright={{ACM}},
	att_copyright_notice={{}},
	att_donotupload={},
	att_private={false},
	att_projects={},
	att_tags={},
	att_techdoc={true},
	att_techdoc_key={TD:102036},
	att_url={http://web1.research.att.com:81/techdocs_downloads/TD:102036_DS1_2017-06-04T00:19:09.723Z.pdf},
	author={Bo Han and Wenxiao Zhang and Pan Hui},
	institution={{ACM SIGCOMM VR/AR Network 2017 Workshop}},
	month={August},
	title={{On the Networking Challenges of Mobile Augmented Reality}},
	year=2017,
}