an object's colors, allowing an operator to ask the software to "zoom in on that red thing," for example. The software will comply, even though the soda can in the example is both red and silver and overlaid with shadows. Nelson is also working on ways to get a computer to recognize an object on sight. One of the tasks he recently gave his students was to set up a game where teams tried to "steal" objects from each other's table while the tables were being monitored by smart cameras. The students would find new ways to defeat the software, and Nelson would then develop new upgrades to the system SO it couldn't be fooled again. Although a six-month-old baby can distinguish various objects from dif- ferent angles, getting a computer to perform this task requires a formidable amount of processing, particularly if the object is located in a complicated natural setting, like a room bustling with activity. Unlike a baby, the software needs to be told a lot about an object before it's able to discern it. Depend- ing on how complex an object is, the software may need anywhere from 1 to 100 photos of the object from different angles. Something very simple, like a piece of paper, can be "grasped" by the program with a single picture; a soda can may require a half-dozen images. A complex object, like an ornate lamp, may need dozens of photographs taken from different angles to capture all its facets. Nelson's software is able to handle this work within seconds. The soft- ware quickly matches any new object it sees with its database of images to determine what the new object is. The smart camera technology has been licensed to PL E-Communications, a Rochester, N.Y.-based company that plans to develop the technology to control video cameras for security applications. CEO Paul Simpson is already looking into using linked cameras, covering a wide area, to exchange infor- mation about certain objects, be they suspicious packages in an airport or a suspicious truck driving through a city under military control. Even unmanned THE 