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In a manually operated visual tracking system, a camera operator follows an object of interest by moving the camera, then gains additional details about the object by zooming in. As the active vision field progresses, the ability to automate such a system is nearing fruition. One hurdle limiting the deployment of real-time visual tracking systems is in the object recognition algorithms that often have restrictive scale and pose requirements. If those conditions are not met, the performance of the system rapidly degrades to failure. The ability of an automatic fixation system to capture quality video of a non cooperative moving target is strongly related to the response time of the mechanical pan, tilt, and zoom platform. However, the price of such a platform rises with its performance. The goal of this work is to investigate the feasibility and issues that arise when using inexpensive off-the-shelf components in the development of a visual tracking system that provides scale-invariant tracking. One of the main challenges is in the zooming action. Optical zoom acts as a measurement gain, amplifying both resolution and tracking error. Previous work has shown that adding a second camera with fixed focal length can assist the zooming camera if it loses fixation, effectively bounding the error. Furthermore, optical zoom has a longer time-constant than digital zoom. This work proposes a dual camera hybrid zoom configuration where digital zoom is combined with optical zoom to achieve a behavior closer to an ideal zooming action.

Zoom techniques for achieving scale invariant object tracking in real-time active vision systems