The software, which uses an 'artificial net' to map key features of the face, can evaluate the intensities of multiple different facial expressions simultaneously.
"Using computational methods to detect facial expressions from video data can be very accurate, when the videos are of high quality and represent optimal conditions -- for instance, when videos are recorded in rooms with good lighting, when participants are sat face-on with the camera, and when glasses or long hair are kept from blocking the face.
They then used an 'automated facial coding' software to computationally analyse parents' facial expressions in the videos and had human coders analyse the facial expressions in the same videos. Professor Rebecca Pearson from Manchester Metropolitan University, co-author and PI of the ERC project explained:"These conditions could be better understood through subtle nuances in parents' facial expressions, providing early intervention opportunities that were once unimaginable. For example, most parents will try to 'mask' their own distress and appear 'ok' to those around them.
As an extension to the ERC project, headcam data is now being collected in teenagers, with the plan to use the same methods to understand complex teen emotions at home, see Teencam Pilot Study -- Institute of Population Health -- University of Liverpool.
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