By analyzing a person's body language, gait and other movements, behavior recognition software is helping catch criminals and may be useful in the war on terror, as well as have medical applications

January 05, 2007|By Frank D. Roylance | Frank D. Roylance,Sun reporter

It's 11:30 at night on Lovegrove Street, an alley near the Homewood campus of the Johns Hopkins University.

A lone man is looking up and down the street, apparently waiting for someone. A pickup truck drives up. The man says something to the driver, gets in and they drive off.

Minutes later, a block away, a woman is robbed at gunpoint by two men who speed off in a pickup. No one at the scene can describe the truck to campus security officers or to Baltimore police.

This case last June might have gone cold. But it did not. The Lovegrove caper was solved by technology that plays the role of an old-fashioned tipster.

Behavior recognition software enables computers to alert people when something, or someone, appears suspicious. The Hopkins system employs one application of the technology to watch for aberrant movements captured by dozens of cameras - far more than any person could track.

Computer analysis of the way people and objects appear and move on video is also being developed at the University of Maryland's A. James Clark School of Engineering and elsewhere for use in surveillance, security, anti-terrorism and even medical applications.

Hopkins' security system caught the robbery suspects on a video camera on Lovegrove Street. The software registered the man's behavior and the late hour, and alerted the security officer on duty in the command center.

The view down Lovegrove was singled out by the computer amid the incoming imagery from 89 campus security cameras. It popped automatically onto the officer's screen, with the man's image highlighted in a yellow box. She quickly zoomed in and recorded images of the suspect, the truck and its license plate.

After the victim reported the robbery, the tag number led police within hours to a borrowed truck and the suspect, who had a police record. The victim picked him out of a photo lineup. He was arrested a few days later, linked to a second crime and charged with both.

"If we didn't have this video system, or she didn't focus on him, he would have gotten away," said Edmund Skrodzki, executive director for security for Hopkins' Homewood campus. "One person can't monitor 89 screens. You need help with it, and behavioral recognition provides that assistance."

The technology has attracted interest and research dollars from the Pentagon and the Department of Homeland Security. Some of that money has gone to the University of Maryland, College Park, where Rama Chellappa is a professor of electrical and computer engineering and director of UM's Center for Automation Research. He is exploring more sophisticated ways to flag people and suspicious activity.

One way is by their gait. The way people move while walking can reveal a lot, Chellappa said.

Is this person male or female? Are his arms both swinging, or is he carrying something? How tall is he? How heavy? How heavy does his burden appear to be? Is it in view or hidden? Has he put it down and walked away?

The computer may even calculate whether this is a gait "signature" it has seen before. Do we know this person?

Some Americans might also want to ask whether this sort of public surveillance and scrutiny is a good thing, or a threat to privacy. At Hopkins, Skrodzki said he's had no complaints. "If anything, we've actually gotten a lot of feedback from faculty, students and staff saying we've increased their comfort level," he said.

Hopkins' camera system is watching a 140-acre campus and nearby areas - up from 32 cameras when Skrodzki was hired in mid-2005. It displays 19 scenes at any one time on a large screen in the command center.

The software was developed by Cernium Corp., an electronic security firm in Reston, Va. It alerts security personnel to 18 behaviors. Among them: people moving very fast or loitering; cars that stop suddenly or drive too fast; crowds that gather or disperse; unattended objects and people who fall.

In addition to the Lovegrove loiterer, the system has alerted security to a juvenile as he attempted to steal a motorbike, leading to an arrest. Another youth was spotted, tracked by cameras and arrested after spray-painting graffiti on campus buildings.

A nighttime bicycle thief was confronted after another alert brought nearby security officers to the scene. The crook dropped his bolt cutters and ran off, but the bike was recovered, Skrodzki said.

Other potential criminals were warned off because of automated alerts as they cased a sorority house, or tried doorknobs and car handles near campus.

"It's been fantastic for us," Skrodzki said. "We are responding more to alerts, and that's a good thing because our whole thing is prevention."

Campus bike thefts dropped from 25 during the 2005 fall semester to three last fall. Overall crime was down 20 percent in 2006. And Skrodzki credits the behavioral recognition software for providing a critical assist.

The Pentagon and Homeland Security have bigger fish to fry, of course.

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