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More than 100 years since the development of movies, film, and television, we have entered a new age of media, the surveillance era. Previously, media was used to entertain, or inform (news). Today, we are also increasingly collecting media to inform ourselves about who, what, and where. Public places from malls to airports to city streets are laced with cameras that watch us with hidden eyes. Home security systems now routinely embed cameras both in and around residences. Autonomous vehicles represent a massive new use of sensors, including RGB, infrared, and lidar. And there are eyes in the skies, not only over military battlespaces, but even over urban areas, as personal drones compete with package delivery robots. All of this surveillance video has a purpose (e.g., object detection, face recognition, object tracking, activity recognition), which is increasingly pursued by machines, not human observers. In the era of surveillance, what does the quality of video mean? One simple answer is: video quality is a measure of how well it supports the purpose. This is in an abstract sense the same as it is for entertainment video. But quantifying it requires new tools. In this paper, we address the case of surveillance, especially aerial surveillance. Our ideas apply equally to military and commercial applications like autonomous vehicles and package delivery.
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