Robust image-based motion stabilization is developed to enable visual surveillance in the maritime domain. The
algorithm developed is neither a dense registration method nor a traditional feature-based method, but rather it captures
the best aspects of each of these approaches. It avoids feature tracking and so can handle large intra-frame motions, and
at the same time it is robust to large lighting variations and moving clutter. It is thus well-suited for challenges in the
maritime domain. Advantage is taken of the maritime environment including use of the horizon and shoreline, and fused
data from an inexpensive inertial measurement unit. Results of real-time operation on an in-water buoy are presented.
Existing maritime navigation and reconnaissance systems require man-in-the-loop situation awareness for obstacle avoidance, area survey analysis, threat assessment, and mission re-planning. We have developed a boat with fully autonomous navigation, surveillance, and reactive behaviors. Autonomous water navigation is achieved with no prior maps or other data − the water surface, riverbanks obstacles, movers and salient objects are discovered and mapped in real-time using a circular array of cameras along with a self-directed pan-tilt camera. The autonomous boat has been tested on harbor and river domains. Results of the detection, tracking, mapping and navigation will be presented.