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Accurate and infrastructure-free indoor positioning can be very useful in a variety of applications. However, most existing approaches (e.g., WiFi and infrared-based methods) for indoor localization heavily rely on infrastructure, which is neither scalable nor pervasively available. In this paper, we propose a novel indoor localization and tracking approach, termed VMag, that does not require any infrastructure assistance. The user can be localized while simply holding a smartphone. To the best of our knowledge, the proposed method is the first exploration of fusing geomagnetic and visual sensing for indoor localization. More specifically, we conduct an in-depth study on both the advantageous properties and the challenges in leveraging the geomagnetic field and visual images for indoor localization. Based on these studies, we design a context-aware particle filtering framework to track the user with the goal of …