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the computer amassed the information

Pawan Sinha, a cognitive scientist at the Massachusetts Institute of Technology, has devoted years of research to figuring out just what attributes touch off these face-specific pings. Security software that is being developed for identifying potential terrorists or detecting intruders must be able to reliably recognize faces. In teaching the software to do this, Dr. Sinha and his colleagues have arrived at unexpected insights into the question of why we sometimes see a cinnamon bun as a cinnamon bun, and other times as the earthly incarnation of a sainted nun.

A grilled cheese sandwich, top, with an image of what some see as the Virgin Mary sold for $28,000 on eBay. Jesus Christ is seen in an oyster shell, a frying pan and a pirogi.CreditGolden Palace.com; Oyster shell: Denis Balibouse/Reuters

To develop detector software optimized to pick out any human face, even in less-than-ideal surroundings, Dr. Sinha began by putting into his computer hundreds of faces as varied as those in a Benetton advertisement famous for its diversity.

As the computer amassed the information, it was able to discover relationships that were of great significance to almost all faces, but very few nonfaces. “These turn out to be very simple relationships, things like the eyes are always darker than the forehead, and the mouth is darker than the cheeks,” Dr. Sinha said. “If you put together about 12 of these relationships, you get a template that you can use to locate a face.”

Most people think of the cartoon smiley face, with its discrete eyes, nose and mouth, as the quintessential face template, but Dr. Sinha’s computer can identify faces even when the pictures are of low resolution.

When he presented human subjects with blurry face images, containing only 12 by 14 pixels’ worth of visual information, they performed similarly well, recognizing 75 percent of the face images accurately. This suggests that like the computer, the human brain processes faces holistically, like coherent landscapes, rather than one feature at a time.

These images are just “ dark blobs on a big blob,” Dr. Sinha said. “So clearly there’s not enough diagnostic information in the individual features. Yet something about the overall organization of the image, the gestalt, is still allowing us to recognize the face.”

Once in a while, the computer emits a false alarm. “This is a good analogy for what the human brain might be doing,” Dr. Sinha said. “Like the computer, it’s trying to determine what the regularities are in all of these faces to create a prototype.