Facial recognition to discover how pigs feel
● SRUC hopes to develop tool to monitor pigs health and wellbeing
Scientists are using facial recognition technology to assess p i g s’ e mo t i o n a l s t a t e s i n a project to help improve animal wellbeing.
Researchers hope that being able to tell from a pig’s express i o n i f i t i s c o n t e n t o r d i s - tressed will lead to the development of a tool that can monitor individual faces and alert farmers to any health and welfare problems.
Pigs are highly expressive and previous research from S c o t l a n d ’s R u r a l C o l l e g e (SRUC) has shown they can signal their intentions to other pigs using different facial expressions.
There is also evidence they make different expressions when in pain or under stress.
In the new project, scientists at SRUC’S Pig Research Centre in Midlothian are capturing 3D and 2D facial images of the breeding sow population under typical situations that are likely to result in different emotional states.
Sows can experience lameness and could show different facial expressions relating to pain b efore and after being given pain relief, while pigs appear calm and content when satiated, which could be reflected in their facial express i o n s . The images are then processed at the University of the West of England Bristol’s Centre for Machine Vision, where various state-of-the-art machine learning techniques are being developed to automati c a l l y i d e nt i f y d i f f e r e nt emotions conveyed by particular facial expressions.
Dr Emma Baxter from SRUC said: “Early identification of pig health issues gives farmers the potential to improve animal wellbeing by tackling a ny p r o b l e m s q u i c k l y a n d implementing tailored treat- me n t f o r i n d i v i d u a l s . T h i s will reduce production costs by preventing impact of health issues on performance.
“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.
“T h i s a l l o ws i n s i g h t i n t o b ot h s ho r t- te r m e moti o n al reactions and long-term indiv i d u a l ‘ m o o d s’ o f a n i m a l s under our care.”
A f t e r va l i d a t i n g t h e t e c h - niques, the team will develop the technology for use on farms with commercial partners where individual sows in large herds will be monitored continuously.
P r o f e s s o r M e l v y n S m i t h from UWE Bristol’s Centre for Machine Vision, par t of the Bristol Robotics Laborator y, said: “Our next step will be, for the first time, to explore the potential for using machine vision to automatically rec - ognise facial expressions that are linked with core emotion states, such as happiness or distress, in the identified pigs.”