Paper Info
Title
Wi-Vi Fingerprint: Wifi And Vision Integrated Fingerprint For Smartphone-Based Indoor Self-Localization
Abstract
Due to limited access to GPS signals, accurate and reliable localization still remains an open problem in indoor environments. This paper proposed a novel WiFi and Vision integrated fingerprint (Wi-Vi Fingerprint) for accurate and robust indoor localization. The method consists of two steps of fingerprint mapping and fingerprint localization. In the mapping step, the Wi-Vi fingerprints for all the sampling positions are computed by using EXIT signs as landmarks. In the localization step, a multi-scale localization strategy is proposed, which includes coarse localization with WiFi matching, image-level localization with visual matching, and finally metric localization for localization refinement. The proposed method has been tested in an indoor office building of 11,200 m(2) with different types of smartphones. Experimental results demonstrate that the proposed method can achieve 96% site recognition rates for image-level localization. The final localization errors after metric localization are less than half meter in average.
Year
Venue
Keywords
2017
2017 24TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP)
Indoor self-localization, visual features, Wi-Vi fingerprint, multi-scale localization
Field
DocType
ISSN
Computer vision,Self localization,Pattern recognition,Computer science,Fingerprint,Sampling (statistics),Visual matching,Artificial intelligence,Metre (music),GPS signals
Conference
1522-4880
Citations 
PageRank 
References 
0
0.34
0
Authors
4
Name
Order
Citations
PageRank
Zhaozheng Hu1144.31
Gang Huang211.03
Yuezhi Hu300.34
Zhe Yang416413.29