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A team of researchers has developed a tool that automatically identifies deepfake photos by analysing light reflections in the eyes.</p>
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The tool proved 94 per cent effective in experiments described in a paper accepted at the IEEE International Conference on Acoustics, Speech and Signal Processing.</p>
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&quot;The cornea is almost like a perfect semisphere and is very reflective,&quot; said the lead author, Siwei Lyu from University at Buffalo.</p>
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&quot;So, anything that is coming to the eye with a light emitting from those sources will have an image on the cornea. The two eyes should have very similar reflective patterns because they&#39;re seeing the same thing. It&#39;s something that we typically don&#39;t typically notice when we look at a face,&quot; Lyu, added.</p>
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For the study, the research team obtained real images from Flickr Faces-HQ, as well as fake images from a repository of AI-generated faces that look lifelike but are indeed fake.</p>
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All images were portrait-like (real people and fake people looking directly into the camera with good lighting) and 1,024 by 1,024 pixels.</p>
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The tool works by mapping out each face. It then examines the eyes, followed by the eyeballs and lastly the light reflected in each eyeball.</p>
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It compares in incredible detail potential differences in shape, light intensity and other features of the reflected light, the team said.</p>
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While promising, the technique has limitations. For one, you need a reflected source of light. Also, mismatched light reflections of the eyes can be fixed during editing of the image, the team said.</p>
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Additionally, the technique looks only at the individual pixels reflected in the eyes – not the shape of the eye, the shapes within the eyes, or the nature of what&#39;s reflected in the eyes, they added.</p>
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(IANS)</p>
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