Wi-Fi and Keygraphs for Localization with Cell Phones

We present a mobile device application that uses information from Wi-Fi signals and from the device's camera to help the localization estimation in indoor environments. The application runs entirely on the mobile device without relying on an external server to achieve real-time performance. The estimation of the localization using camera information is accomplished by keygraph matching between previously selected sign images whose location are known in the environment. The estimation of the Wi-Fi localization is implemented using a naive Bayes classifier on the signals of existing local wireless networks. The final estimation is achieved by using the latter as a rougher estimation of the device location while no sign is detected and, when the device gets closer to a sign, by using the camera to refine the initial Wi-Fi estimation to obtain a much more precise localization. We show results obtained with our approach on a local indoor environment.