UK university evaluates police face recognition efforts
28 November 2018 15:15 GMT

Academics at Cardiff University's Crime and Security Research Institute have conducted the first independent academic evaluation of Automated Facial Recognition (AFR) technology across a variety of major policing operations.

The project by the Universities’ Police Science Institute evaluated South Wales Police’s deployment of Automated Facial Recognition across several major sporting and entertainment events in Cardiff city over more than a year, including the UEFA Champion’s League Final and the Autumn Rugby Internationals.

The study found that while AFR can enable police to identify persons of interest and suspects where they would probably not otherwise have been able to do so, considerable investment and changes to police operating procedures are required to generate consistent results.  

Researchers employed a number of research methods to develop a rich picture and systematically evaluate the use of AFR by police across multiple operational settings. This is important as previous research on the use of AFR technologies has tended to be conducted in controlled conditions. Using it on the streets and to support ongoing criminal investigations introduces a range of factors impacting the effectiveness of AFR  in supporting police work.

The technology works in two modes: Locate is the live, real-time application that scans faces within CCTV feeds in an area. It searches for possible matches against a pre-selected database of facial images of individuals deemed to be persons of interest by the police.

Identify, on the other hand, takes still images of unidentified persons (usually captured via CCTV or mobile phone camera) and compares these against the police custody database in an effort to generate investigative leads. Evidence from the research found that in 68% of submissions made by police officers in the Identify mode, the image was not of sufficient quality for the system to work.

Over the period of the evaluation, however, the accuracy of the technology improved significantly and police got better at using it. The Locate system was able to correctly identify a person of interest around 76% of the time. A total of 18 arrests were made in ‘live Locate deployments during the evaluation, and in excess of 100 people were charged following investigative searches during the first 8-9 months of the AFR Identify operation (end of July 2017-March 2018).

The report suggests that it is more helpful to think of AFR in policing as 'Assisted Facial Recognition' rather than a fully 'Automated Facial Recognition' system. ‘Automated’ implies that the identification process is conducted solely by an algorithm, when in fact, the system serves as a decision-support tool to assist human operators in making identifications. Ultimately, decisions about whether a person of interest and an image match are made by police operators. It is also deployed in uncontrolled environments, and so is impacted by external factors including lighting, weather and crowd flows.