enhancing wifibased localization with visual clues

The objectives of this paper are to review existing literature discussing location information quality and to provide a consistent framework for describing and dealing with location information quality. In the literature, the quality of location information has been defined in different ways based on varying sets of aspects. Extensive experiments show that Argus triples the localization accuracy of classic RSS-based method, in time no longer than normal WiFi scanning, with negligible energy consumption.The quality of location information is an important factor for location-based services (LBSs). We devise techniques for photo selection, geometric constraint extraction, joint location estimation, and build a prototype that runs on commodity phones.

The basic idea of Argus is to extract geometric constraints from crowdsourced photos, and to reduce fingerprint ambiguity by mapping the constraints jointly against the fingerprint space. To get over these limitations, we propose Argus, an image-assisted localization system for mobile devices. Though pioneer efforts have resorted to motion-assisted or peer-assisted localization, they neither work in real time nor work without the help of peer users, which introduces extra costs and constraints, and thus degrades their practicality. However, those methods suffer from fingerprint ambiguity that roots in multipath fading and temporal dynamics of wireless signals. Current mainstream solutions rely on Received Signal Strength (RSS) of wireless signals as fingerprints to distinguish and infer locations. Indoor localization is of great importance to a wide range of applications in the era of mobile computing. text application/pdf info:doi/10.1145/2750858.2807516 Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Indoor Localization Smart Phone Photogrammetry Digital Communications and Networking Information SecurityĮnhancing WiFi-based localization with visual clues Extensive experiments show that Argus triples the localization accuracy of classic RSS-based method, in time no longer than normal WiFi scanning, with negligible energy consumption.

Sg-smu-ink.sis_research-5753 Enhancing WiFi-based localization with visual clues XU, Han YANG, Zheng ZHOU, Zimu SHANGGUAN, Longfei LIU, Yunhao YI, Ke Indoor localization is of great importance to a wide range of applications in the era of mobile computing.

Enhancing wifibased localization with visual clues