一种面向大型室内场景的高可用手机视觉全局定位方法  

A Visual Global Positioning Method Based on Smartphone with High Usability in Large Indoor Spaces

作　　者：柳景斌 郭英晖 喻文慧 LIU Jingbin;GUO Yinghui;YU Wenhui(State Key Laboratory of Information Engineering in Surveying,Mapping and Remote Sensing,Wuhan University,Wuhan 430079,China;School of Geodesy and Geomatics,Wuhan University,Wuhan 430079,China)

机构地区：[1]武汉大学测绘遥感信息工程国家重点实验室,湖北武汉430079 [2]武汉大学测绘学院,湖北武汉430079

出　　处：《武汉大学学报（信息科学版）》2024年第12期2301-2312,共12页Geomatics and Information Science of Wuhan University

基　　金：国家自然科学基金(42474060);湖北省自然科学基金(2024AFD403);武汉市重点研发计划人工智能创新专项(2023010402040029);武汉大学测绘遥感信息工程国家重点实验室自主科研课题资助。

摘　　要：基于视觉的手机定位方法是室内定位中的研究热点,但面向机场、商场等大型室内环境时存在可靠性差、计算效率低等问题。针对该类场景,提出一种基于三维实景地图的粗定位-精定位二级定位方法,首先基于Wi-Fi指纹匹配粗定位结果约束匹配图像库范围,然后通过子区域分段式建立特征库以及利用深度学习的方法去除天花板图像。实验结果表明,大型室内场景下所提方法可以将视觉匹配定位精度由1.89 m提升至0.45 m,将定位计算效率提升5倍以上。所提方法能够有效降低定位时间,提升特征点云的精度,进而提升视觉匹配定位精度,同时能降低特征点匹配错误而造成定位错误的情况,可以实现高可用、亚米级精度的室内视觉全局定位。Objectives:The visual global positioning based on smartphone is a research hotspot in location community services.The existing methods suffer from the problems of poor reliability and low computing efficiency especially when they are used for large indoor environments such as airport and shopping mall.Methods:This paper proposes a two-level localization method including rough localization and accurate lo-calization,which is based on 3D real map and applied to large indoor scenes such as shopping mall.To re-duce the location computing time,this paper proposes a method to limit the scope of image database.Wi-Fi fingerprint matching algorithm is used to obtain the location results,and then limit the image database.In order to improve the positioning accuracy,a new method of constructing database is proposed.The whole scene is divided into multiple regions,and each region completes the database establishment indepen-dently and splices different databases.In order to reduce the location error,a scene recognition method is proposed.Deep learning method is used to remove the ceiling images and reduce the matching errors of fea-ture points.Results:By comparing the location computing time before and after limiting the scope of image database,the proposed method improves the positioning precision from 1.89 m to 0.45 m,and reduces the positioning time from 6.113 s to 0.827 s per image.Conclusions:The proposed method achieves sub-meter accuracy of indoor vision global positioning,while the feature points matching errors affect the positioning precision.In the future work,feature lines will be used to improve the positioning accuracy.

关 键 词：室内定位 视觉定位 智能手机定位 智能手机导航 全局定位 

分 类 号：P237[天文地球—摄影测量与遥感]