Learning pig facial expressions could help with care

New technology can read expressions on pigs’ faces to gauge if they really are as happy as they are made out to be.

Pigs are emotive and flaunt their feelings frequently with different facial expressions easily read by other pigs but not usually easily recognized by humans.

Being able to read those expressions could help fight disease and improve animal health and welfare.

Animal behaviourists from Scotland’s Rural College in Edinburgh have teamed up with machine vision experts at the University of the West of England (UWE Bristol) for the study, which it is hoped will lead to a tool that can monitor individual animal faces and alert farmers to health and welfare problems.

SRUC research has previously shown pigs can signal their intentions to other pigs using different facial expressions. There is also evidence of different expressions when they are in pain or under stress.

At SRUC’s Pig Research Centre near Edinburgh, scientists are capturing 3D and 2D facial images of the breeding sow population under various, typical commercial situations that are likely to result in different emotional states.

For example, sows can experience lameness and could show different facial expressions relating to pain before and after being given pain relief.

Detecting a positive emotional state is more novel, but sows are highly food motivated and appear calm and content when satiated. They hope this mood could be reflected in sows’ facial expressions.

Images are then processed at UWE Bristol’s Centre for Machine Vision, where various techniques are being developed to automatically identify different emotions conveyed by particular facial expressions.

After validating these techniques, the team hopes to develop the technology for on-farm use with commercial partners where individual sows in large herds will be continuously monitored.

“Machine vision technology offers the potential to realize a low-cost, non-intrusive and practical means to biometrically identify individual animals on the farm,” Melvyn Smith from UWE said.

“Our work has already demonstrated a 97 percent accuracy at facial recognition in pigs. Our next step will be, for the first time, to explore the potential for using Machine Vision to automatically recognize facial expressions that are linked with core emotion states, such as happiness or distress, in the identified pigs.”

Emma Baxter from SRUC said early detection of any health issues can give farmers the ability to tackle problems early.

“This will reduce production costs by preventing impact of health issues on performance,” she said.

“By focusing on the pig’s face, we hope to deliver a truly animal-centric welfare assessment technique, where the animal can ‘tell’ us how it feels about its own individual experiences and environment. This allows insight into both short-term emotional reactions and long-term individual moods of animals under our care.”

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