How effective is human video surveillance performance?

In surveillance situations, computer vision systems are often deployed to help humans perform their tasks more effectively. In a typical installation human observers are required to simultaneously monitor a number of video signals. Psychophysical research indicates that there are severe limitations in the ability of humans to monitor simultaneous signals. Do these same limitations extend to surveillance? We present a method for evaluating human surveillance performance in a situation that mimics demands of real world surveillance. A single computer monitor contained either nine display cells or four display cells. Each cell contained a stream of 2 to 4 moving objects. Observers were instructed to signal when a target event occurred - - when one of the objects entered a small square ldquoforbiddenrdquo region in the center of the display. Target events could occur individually or in groups of 2 or 3 temporally close events. The results indicate that the observers missed many targets (60%) when required to monitor 9 displays and many fewer when monitoring 4 displays (20%). Further, there were costs associated with target events occurring in close temporal succession. Understanding these limitations would help computer visions researchers to design algorithms and human-machine interfaces that result in improved overall performance.