Exploring the Evolution of Mobile Augmented Reality for Future Entertainment Systems

Author:

Pucihar Klen Čopič1,Coulton Paul1

Affiliation:

1. Lancaster University, School of Computing and Communications, UK

Abstract

Despite considerable progress in mobile augmented reality (AR) over recent years, there are few commercial entertainment systems utilizing this exciting technology. To help understand why, we shall review the state of the art in mobile AR solutions, in particular sensor-based, marker-based, and markerless solutions through a design lens of existing and future entertainment services. The majority of mobile AR that users are currently likely to encounter principally utilize sensor-based or marker-based solutions. In sensor-based systems, the poor accuracy of the sensor measurements results in relatively crude augmentation, whereas in marker-based systems, the requirement to physically augment our environment with fiducial markers limits the opportunity for wide-scale deployment. While the alternative online markerless systems overcome these limitations, they are sensitive to environmental conditions (i.e. light conditions), are computationally more expensive, and present greater complexity of implementation, particularly in terms of their system-initialization requirements. To simplify the operation of online markerless systems, a novel, fully autonomous map initialization method based on accelerometer data is also presented; when compared with alternative move-matching techniques, it is simpler to implement, more robust, faster, and less computationally expensive. Finally, we highlight that while there are many technical challenges remaining to make mobile AR development easier, we also acknowledge that because of the nature of AR, it is often difficult to assess the experience that mobile AR will provide to users without resorting to complex system implementations. We address this by presenting a method of creating low-fidelity prototypes for mobile AR entertainment systems.

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Science Applications

Cited by 17 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3