LAUSR

Indoor localization has been an active research area in the last decade. Various localization systems have been proposed based on different types of signals, including but not limited to WiFi, ultrawideband, inertial measurements, and visual signals. Fingerprinting-based methods are among the most popular methods due to their accuracy and ease of deployment. However, a disadvantage to fingerprinting-based methods is the training phase in which fingerprints have to be collected at known locations and stored for future localization inquiries. Recently a few methods have been proposed to alleviate this problem. In this paper, we focus on the possibility of reducing the burden of the training phase for visual (image-based) indoor localization systems by proposing a system that automatically generates the image-location database. The proposed system will be referred to as automatic visual fingerprinting that can be paired with any indoor image-based localization method. We will also validate the proposed system through extensive experiments.