Dual camera system for acquisition of high resolution images
Jeremie A. Papon, Randy P. Broussard, Robert W. Ives · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2007
Video surveillance is ubiquitous in modern society, but surveillance cameras are severely limited in utility by their low resolution. With this in mind, we have developed a system that can autonomously take high resolution still frame images of moving objects. In order to do this, we combine a low resolution video camera and a high resolution still frame camera mounted on a pan/tilt mount. In order to determine what should be photographed (objects of interest), we employ a hierarchical method which first separates foreground from background using a temporal-based median filtering technique. We then use a feed-forward neural network classifier on the foreground regions to determine whether the regions contain the objects of interest. This is done over several frames, and a motion vector is deduced for the object. The pan/tilt mount then focuses the high resolution camera on the next predicted location of the object, and an image is acquired. All components are controlled through a single MATLAB graphical user interface (GUI). The final system we present will be able to detect multiple moving objects simultaneously, track them, and acquire high resolution images of them. Results will demonstrate performance tracking and imaging varying numbers of objects moving at different speeds.