Estimating Sheep Pain with Facial Recognition

Animals can't tell us when they're experiencing pain, so we have to rely on other cues to help treat their discomfort. But it is often difficult to tell how much an animal is suffering. The sheep, for instance, is the most inscrutable of animals. However, scientists have figured out a way to understand sheep facial expressions using artificial intelligence.

On this week's episode, Dr. Marwa Mahmoud from the University of Cambridge joins us to discuss her recent study, "[Estimating Sheep Pain Level Using Facial Action Unit Detection](http://www.cl.cam.ac.uk/~pr10/publications/fg17.pdf)." Marwa and her colleague's at Cambridge's Computer Laboratory developed an automated system using machine learning algorithms to detect and assess when a sheep is in pain. We discuss some details of her work, how she became interested in studying sheep facial expression to measure pain, and her future goals for this project.

If you're able to be in Minneapolis, MN on August 23rd or 24th, consider attending Farcon. Get your tickets today via [https://farcon2017.eventbrite.com](https://farcon2017.eventbrite.com).

Guest

Marwa Mahmoud: I am a research fellow of King's college. I work at the Graphics and Interaction group and I am an affiliated lecturer at the Department of Computer Science and Technology. I teach the assessment module for the MPhil Computer Vision course. My research focuses on vision-based artificial Intelligence and multimodal signal processing within the contexts of affective Computing, behaviour analytics and human (and animal) behaviour understanding. I am particularly interested in building inference models that tackle challenging real-world problems, which are usually characterised by data scarcity and noisy signals from multiple modalities.