通过VSLAM和谷歌街景增强户外基于位置的增强现实准确度
Komang Candra Brata1,2, Nobuo Funabiki1, Yohanes Yohanie Fridelin Panduman1
1Graduate School of Natural Science and Technology, Okayama University, Okayama 700-8530, Japan.
Sensors (Basel, Switzerland)
|February 24, 2024
概括
这项研究通过将视觉同时定位和映射 (VSLAM) 与谷歌街景 (GSV) 结合起来,增强了户外基于位置的增强现实 (LAR). 这种方法比传统的GPS方法显著提高了AR准确度.
科学领域:
- 计算机视觉 计算机视觉
- 地理信息系统 (GIS) 是一个地理信息系统.
- 增强现实是一种增强现实.
背景情况:
- 户外基于位置的增强现实 (LAR) 需要高定位精度来整合虚拟内容.
- 使用全球定位系统 (GPS) 和指南针的传统方法往往缺乏准确的AR对齐所需的精度.
- 现有的LAR应用中的传感器融合技术在实现精确的真实世界AR内容放置方面存在局限性.
研究的目的:
- 引入和评估一种创新的方法,以提高LAR在户外环境中的精度.
- 在户外LAR应用中解决传统传感器融合方法的精度限制.
- 改进增强现实内容与现实环境的调整.
主要方法:
- 利用视觉同步定位和映射 (VSLAM) 技术进行增强的定位.
- 利用基于云的方法与谷歌街景 (GSV) 视觉参考数据库相结合.
- 使用10个感兴趣点 (POI) 作为评估点坐标进行实验.
主要成果:
- 与传统的基于GPS的方法相比,在总体定位准确度方面取得了显著的改进.
- 在现实世界中对准AR内容时实现了卓越的准确性.
- 性能测试证实,拟议的LAR方法的精度和负载处理得到了改进.
结论:
- 集成VSLAM和GSV可以显著提高户外LAR准确度.
- 这种创新方法克服了传统GPS和传感器融合方法的精度限制.
- 这些发现为更具身临其境和准确的户外增强现实体验铺平了道路.
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