SBIR Phase II: New Algorithms for Pan-Tilt-Zoom (PTZ) Camera Based Object Tracking

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This Small Business Innovation Research (SBIR) Phase II project aims to develop a new class of moving object tracking algorithms and software prototype for Pan-Tilt-Zoom (PTZ) cameras in video surveillance systems. In most of today's video surveillance systems, human operators using PTZ cameras perform real-time object tracking manually. This is often stressful and inefficient (an operator can only control one PTZ camera at a time) and causes inconsistent results. The proposed project will develop a new class of algorithms to direct PTZ cameras to track multiple moving objects of interest automatically. Using an optimal filter with new object state and observation models does this. The project outcome will be smart software modules that can be integrated into standard video surveillance systems to improve their capabilities. Video surveillance systems are important tools in the fight against crime and terrorism. Most of the systems on the market today are relatively standard DVR's (digital video recorders) with few smart features. The proposed innovation (automatic object tracking) is a smart feature that can significantly improve a standard system's capabilities by allowing it to get better and more useful images. Since this feature is demanded by many end-users, it is highly attractive to equipment vendors and integrators. Furthermore, by introducing new models for object tracking , the proposed innovation also advances the state-of-the-art in image processing and computer vision research.