Police want to identify these men (Image: Metropolitan Police/AP/PA)

THE response was as aggressive and swift as the riots themselves. Within a few hours of the worst of last week’s looting across London and other English cities, attempts were being made to use CCTV footage to track down the individuals who had plundered shops and destroyed buildings.

But those raised on a diet of TV police dramas who expected crack law enforcement teams to simply plug the footage into a computer and then print out a list of suspects are going to be disappointed. The poor quality of most CCTV footage makes it almost impossible to trust standard automated facial recognition techniques.

One of the most common methods used to help identify an individual from camera footage is photoanthropometry, which uses “proportionality indices” to compare a picture of a suspect on a police database, say, with a CCTV image. Key points on a person’s face – such as the chin, edge of the nose, or centre of the top lip – are marked and the distance between them measured. Someone experienced with this technique can then judge whether the two faces match.


Reuben Moreton from the London Metropolitan Police’s Digital and Electronic Forensic Service tested the techniques on poor quality, low-resolution footage of 13 volunteers. It produced “chaotic, inconsistent results” (Forensic Science, DOI: 10.1016/j.forsciint.2011.06.023). The lack of facial detail reduced the precision of the PI measurements so that individuals with similar PIs could easily be confused with one another.

Imperfect CCTV and poor- quality images can easily thwart more advanced, automated techniques too, says Lyndon Smith at the Machine Vision Laboratory of the University of the West of England, Bristol, UK.

“There is an inherent reliability problem in conventional face recognition systems,” he says. “Changes in lighting, image quality, changing background and orientation – even make-up can fool them.”

Smith’s group is working on a system called Photoface that he believes could help. The system takes a number of 2D images of someone’s face and then stitches them together into a 3D model in which the lighting can be manipulated and the face can be viewed from different angles. He envisages Photoface being used on CCTV footage fed to a police control room. “This is a system that could help with the identification of people in unusual situations or low light,” Smith says.

Graham Cluley, senior technology consultant at IT security firm Sophos, agrees that current systems are not up to the task. “This is not CSI Miami,” he says. “Computers can’t do the things you see on TV shows.”

While a Metropolitan police source told New Scientist that face recognition technology is being used in some cases, it is only effective for face-on shots. It’s far more useful, he says, to post CCTV images of suspected rioters on the Met’s Flickr account, and then invite the public to comb through the images and point out suspects they recognise. “We can get a JPEG in front of a million people in 2 minutes. No computer system can match that at the moment.”

Face recognition works for full-face shots but a JPEG posted on Flickr can reach a million people in 2 minutes

Some digital vigilantes believe face recognition technology will provide the answer. A group of programmers have formed the Google Group “London Riots Facial Recognition”. They won’t discuss their techniques, but told New Scientist: “We’re just a bunch of computer programmers who want to use technology to try and help the situation.”

Make a match on Facebook WHILE CCTV images are tricky to analyse effectively, facial recognition software can still be a powerful tool. At the Black Hat conference in Las Vegas last month Alessandro Acquisti of Carnegie Mellon University in Pittsburgh, Pennsylvania, demonstrated how easy it is to match anonymous photos of people to their Facebook profile pictures. Around 100 student volunteers were asked to peer into a webcam. After just 3 seconds of scanning, off-the-shelf face recognition software linked 31 per cent of the students to their Facebook profile. He also showed it was possible to put a name to the faces of people on a dating website by cross-referencing their pictures with Facebook.