{"title":"一种在线异构定位融合系统的可扩展匹配机制","authors":"Chung-Yuan Chen, Ruey-Beei Wu","doi":"10.1109/RWS53089.2022.9719930","DOIUrl":null,"url":null,"abstract":"Wi-Fi fingerprint positioning has the advantages of being infrastructure-less and easily accessible, but the weaknesses in terms of lower accuracy and limited Wi-Fi scanning speed are also hard to tackle. On the other hand, with the progress in computer vision and deep learning, vision-based positioning based on commonly available surveillance cameras becomes a promising solution for providing location-based services. But the major difficulty lies in checking the identity of detected people just by the captured images. This paper proposed a novel Matching Mechanism to address the identity matching problem, which associates the non-identifiable positioning sources like vision to the easily identifiable positioning sources like smart phone’s Wi-Fi. Practicalities like scalability and online operation are considered in both the design and implementation of the mechanism. As a result, the experiment not only proved the effectiveness of matching the vision-based and Wi-Fi positioning results but also showed an improvement in positioning accuracy by over 60%.","PeriodicalId":113074,"journal":{"name":"2022 IEEE Radio and Wireless Symposium (RWS)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A Scalable Matching Mechanism for Online Heterogeneous Positioning Fusion System\",\"authors\":\"Chung-Yuan Chen, Ruey-Beei Wu\",\"doi\":\"10.1109/RWS53089.2022.9719930\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Wi-Fi fingerprint positioning has the advantages of being infrastructure-less and easily accessible, but the weaknesses in terms of lower accuracy and limited Wi-Fi scanning speed are also hard to tackle. On the other hand, with the progress in computer vision and deep learning, vision-based positioning based on commonly available surveillance cameras becomes a promising solution for providing location-based services. But the major difficulty lies in checking the identity of detected people just by the captured images. This paper proposed a novel Matching Mechanism to address the identity matching problem, which associates the non-identifiable positioning sources like vision to the easily identifiable positioning sources like smart phone’s Wi-Fi. Practicalities like scalability and online operation are considered in both the design and implementation of the mechanism. As a result, the experiment not only proved the effectiveness of matching the vision-based and Wi-Fi positioning results but also showed an improvement in positioning accuracy by over 60%.\",\"PeriodicalId\":113074,\"journal\":{\"name\":\"2022 IEEE Radio and Wireless Symposium (RWS)\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-01-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE Radio and Wireless Symposium (RWS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RWS53089.2022.9719930\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE Radio and Wireless Symposium (RWS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RWS53089.2022.9719930","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Scalable Matching Mechanism for Online Heterogeneous Positioning Fusion System
Wi-Fi fingerprint positioning has the advantages of being infrastructure-less and easily accessible, but the weaknesses in terms of lower accuracy and limited Wi-Fi scanning speed are also hard to tackle. On the other hand, with the progress in computer vision and deep learning, vision-based positioning based on commonly available surveillance cameras becomes a promising solution for providing location-based services. But the major difficulty lies in checking the identity of detected people just by the captured images. This paper proposed a novel Matching Mechanism to address the identity matching problem, which associates the non-identifiable positioning sources like vision to the easily identifiable positioning sources like smart phone’s Wi-Fi. Practicalities like scalability and online operation are considered in both the design and implementation of the mechanism. As a result, the experiment not only proved the effectiveness of matching the vision-based and Wi-Fi positioning results but also showed an improvement in positioning accuracy by over 60%.