Using Cameras to Improve Wi-Fi Based Indoor Positioning

Indoor positioning systems are increasingly being deployed to enable indoor navigation and other indoor location-based services. Systems based on Wi-Fi and video cameras rely on different technologies and techniques and have so far been developed independently by different research communities; we show that integrating information provided by a video system into a Wi-Fi based system increases its maintainability and avoid drops in accuracy over time. Specifically, we consider a Wi-Fi system that uses fingerprints measurements collected in the space for positioning. We improve the system’s room-level accuracy by means of automatic, video-driven collection of fingerprints. Our method is able to relate a Wi-Fi user to unidentified movements detected by cameras by exploiting the existing Wi-Fi system, thus generating fingerprints automatically. This use of video for fingerprint collection reduces the need for manual collection and allows online updating of fingerprints. Hence, increasing system accuracy. We report on an empirical study that shows that automatic fingerprinting induces only few false positives and yields a substantial accuracy improvement.