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Cornell Researchers Created Earphone Tracks Facial Expressions, Even with a Face Mask

Cornell researchers have invented an earphone that can continuously track full facial expressions by observing the contour of the cheeks – and can then translate expressions into emojis or silent speech commands.

With the ear-mounted device, called C-Face, users could express emotions to online collaborators without holding cameras in front of their faces – an especially useful communication tool as much of the world engages in remote work or learning.

“This device is simpler, less obtrusive and more capable than any existing ear-mounted wearable technologies for tracking facial expressions,” said Cheng Zhang, assistant professor of information science and senior author of “C-Face: Continuously Reconstructing Facial Expressions by Deep Learning Contours of the Face With Ear-Mounted Miniature Cameras.”

With C-Face, avatars in virtual reality environments could express how their users are actually feeling, and instructors could get valuable information about student engagement during online lessons. It could also be used to direct a computer system, such as a music player, using only facial cues.

Because it works by detecting muscle movement, C-Face can capture facial expressions even when users are wearing masks, Zhang said.

The device consists of two miniature RGB cameras – digital cameras that capture red, green and bands of light – positioned below each ear with headphones or earphones. The cameras record changes in facial contours caused when facial muscles move.

These reconstructed facial expressions represented by 42 feature points can also be translated to eight emojis, including “natural,” “angry” and “kissy-face,” as well as eight silent speech commands designed to control a music device, such as “play,” “next song” and “volume up.”

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