Visual homing has been widely studied in the past decade. It enables a mobile robot to move to a Home position using only information extracted from visual data. However, integration of homing algorithms into real applications is not widely studied and poses a number of significant challenges. Failures often occur due to moving people within the scene and variations in illumination. We present a novel integrated indoor topological navigation framework, which combines odometry motion with visual homing algorithms. We show robustness to scene variation and real-time performance through a series of tests conducted in four real apartments and several typical indoor scenes, including doorways, offices etc.