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In many mobile robotics applications involving exploration of unknown environments, it would be extremely useful to provide human operators with a real-time 3D visualization of the environment the robot is exploring. Although a great deal of progress has been made in the separate fields of photorealistic structure from motion and realtime vision-based robot localization and mapping (SLAM), the ultimate goal of real-time 3D visualization of the environment a robot is exploring has yet to be realized. In this paper, we present a simple and efficient incremental algorithm for 3D modeling amenable to realtime implementation. The algorithm creates a texture-mapped polygonal mesh model of the environment from a monocular video feed or sequence of images. The key to the algorithm's simplicity and efficiency is the use of the isosurface of a coarse 3D occupancy grid that is incrementally updated as new images arrive. The isosurface-based reconstruction provides low metric accuracy but helps to filter measurement noise and allows rapid construction of a 3D visualization. We demonstrate the practicality and effectiveness of the algorithm by using it to generate an OpenGL model of a real indoor environment.