Conventional daylight video, and other forms of motion imagery, have an expanded role in communication and decision
making as sensor platforms (e.g., unoccupied aerial vehicles [UAVs]) proliferate. Video, of course, enables more
persons to become observers than does direct viewing, and presents a rapidly growing volume of content for those
observers to understand and integrate. However, knowing the identity of objects and gaining an awareness of situations
depicted in video can be challenging as the number of camera feeds increases, or as multiple decision makers rely on the
same content. Graphic additions to streaming video, spatially registered and appearing to be parts of the observed scene,
can draw attention to specific content, reduce uncertainty, increase awareness of evolving situations, and ultimately
produce a type of image-based communication that reduces the need for verbal interaction among observers. This paper
describes how streaming video can be enhanced for decision support using feature recognition and tracking; object
identification, graphic retrieval and positioning; and collaborative capabilities.
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