  The existing localization systems for indoor applications basically rely on
wireless signal. With the massive deployment of low-cost cameras, the visual
image based localization become attractive as well. However, in the existing
literature, the hybrid visual and wireless approaches simply combine the above
schemes in a straight forward manner, and fail to explore the interactions
between them. In this paper, we propose a joint visual and wireless signal
feature based approach for high-precision indoor localization system. In this
joint scheme, WiFi signals are utilized to compute the coarse area with
likelihood probability and visual images are used to fine-tune the localization
result. Based on the numerical results, we show that the proposed scheme can
achieve 0.62m localization accuracy with near real-time running time.
