The scale of the camera networks in surveillance systems has been largely expanded. However, conventional visualization methods display each camera video on an individual screen. In this way, it is difficult to effectively monitor the regions covered by all of the cameras, especially when tracking a moving target crossing different camera views. In this paper, we propose a novel visualization framework for surveillance systems with two distinct features: (1) integration of multiple camera views and a Google Earth satellite image with 3D building models; and (2) a wall-size display with dual resolutions, called e-Fovea, created by combining a fixed projector and a steerable projector whose projection direction can be controlled. Within the large-scale display area projected by the fixed projector, there is a fovea area with high resolution image of a selected camera projected by the steerable projector. To increase the computational efficiency, we adopt CUDA programming for the integration of multiple camera views. Our experimental results demonstrate a practical implementation of the proposed visualization framework for monitoring vehicles moving across multiple camera views surrounding a building. Through the proposed system, the security guard can simultaneously perceive the low-resolution image of large-scale monitored area and focus on the region of interest with high resolution.