Facial Recognition: AI Technology Advances

Protecting sensitive online data has never been of greater importance and developments in AI technology are helping to achieve this. One of the most obvious ways that our data can be compromised is by an unauthorised person gaining access to our mobile devices, which is why protection such as fingerprint- or facial-recognition is so important.

Using AI techniques, a group of researchers from Bradford University have achieved 100% recognition rates, even when only half of the face is visible. The study and its conclusions were published in Future Generation Computer Systems and represents the first such study to use machine learning to improve recognition rates.

Professor Hassan Ugail was the lead researcher on the study. He said: "Computers can already perform better than humans in recognising one face from a large number, so we wanted to see if they would be better at partial facial recognition as well. We've now shown that it's possible to have very accurate facial recognition from images that only show part of a face and we've identified which parts are most useful. This opens up greater possibilities for the use of the technology for security or crime prevention.

The dataset for the study comprised 2,800 photographs of 200 male and female students and staff from Brazil's FEI University. A computer model was first trained using full facial images before the experiment proper began, with the model only being shown half- and three-quarter faces. Though 100% success was achieved with full, three-quarter and top-half facial images, the recognition rate dropped to 60% for images containing only the bottom half of the face and just 40% for images showing only individual facial features such as nose and eyes.

Professor Ugail concluded by saying: "..our experiments now need validating on a much larger dataset. However, in the future it's likely that image databases used for facial recognition will need to include partial images as well, so that the models can be trained correctly to recognise a face even when not all of it is visible.

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