WI-VI fingerprint: WiFi and vision integrated fingerprint for smartphone-based indoor self-localization

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 m² 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.