Biometrics experts are developing a crime-fighting tool that can help law enforcement officials identify suspicious individuals at crime scenes.
Kevin Bowyer and Patrick Flynn of Notre Dame’s Computer Science and Engineering Department have been researching the feasibility of image-based biometrics since 2001, including first-of-their-kind comparisons of face photographs, face thermograms, 3-D face images, iris images, videos of human gait, and even ear and hand shapes.
The researchers developed a “Questionable Observer Detector (QuOD)” to identify individuals who repeatedly appear in video taken of bystanders at crime scenes.
The challenge was especially daunting because the researchers lacked a data base to compare faces against. Also, many times crime scene videos are shot by witnesses using handheld videos and are often of poor quality. Additionally, many criminals try to disguise their appearance in various ways.
In response, the Notre Dame team focused on an automatic facial recognition tool that didn’t need to match people against an existing database of known identities.
Instead, Bowyer, Flynn and Barr create “face tracks” for all individuals appearing in a video and repeat the process for all available video clips.
The face tracks are compared to determine if any faces from different video clips look similar enough to match each other. When the technology spots a match, it adds it to a group of video appearances featuring just that person. In this way, it attempts to cluster together the pieces of different video clips that represent the same person.
An individual is considered suspicious if he or she appears too frequently in the set of videos. The “too many” number is determined by law enforcement officials based on the number of crimes and videos available.
Although the technology shows great promise, Bowyer, Flynn and Barr admit they still have serious technical challenges they are working to overcome.