New Computer Model Recognizes 21 Distinct Facial Expressions
The model is able to map human emotion with greater accuracy than ever before, and perhaps even aid in the diagnosis and treatment of psychological conditions such as autism and post-traumatic stress disorder (PTSD).
“We’ve gone beyond facial expressions for simple emotions like ‘happy’ or ‘sad.’ We found a strong consistency in how people move their facial muscles to express 21 categories of emotions,” said Aleix Martinez, Ph.D., a cognitive scientist and associate professor of electrical and computer engineering at Ohio State.
“That is simply stunning. That tells us that these 21 emotions are expressed in the same way by nearly everyone, at least in our culture.”
For centuries, scholars have attempted to figure out how and why our faces give away our feelings — from happy to sad, and the variety of emotions in between and beyond. Today, the research has been taken up by cognitive scientists who want to link facial expressions to emotions in order to track the genes, chemicals, and neural pathways that manage emotion in the brain.
“Until now, cognitive scientists have limited their research to six basic emotions—happy, sad, fearful, angry, surprised, and disgusted — mostly because the facial expressions for them were thought to be self-evident,” Martinez explained.
“But,” Martinez said, “decoding a person’s brain functioning with only six categories is like painting a portrait with only primary colors — it can provide an abstracted image of the person, but not a realistic one.”
“In cognitive science, we have this basic assumption that the brain is a computer. So we want to find the algorithm implemented in our brain that allows us to recognize emotion in facial expressions,” he said.
“In the past, when we were trying to decode that algorithm using only those six basic emotion categories, we were having tremendous difficulty. Hopefully with the addition of more categories, we’ll now have a better way of decoding and analyzing the algorithm in the brain.”
During the study, they photographed 230 volunteers (mostly college students) — 130 female, 100 male — making faces in response to verbal cues such as “you just got some great unexpected news” (happily surprised), or “you smell a bad odor” (disgusted).
As the researchers sorted through the resulting 5,000 images, they painstakingly tagged prominent landmarks for facial muscles, such as the corners of the mouth or the outer edge of the eyebrow. They eventually pinpointed 21 emotions — the six basic emotions, as well as emotions that exist as combinations of those emotions, such as “happily surprised” or “sadly angry.”
The researchers referred to these combinations as “compound emotions.” For example, “happily surprised” might be the emotion expressed when we receive unexpected good news, and “sadly angry” could be the face we make when someone we care about makes us angry.
Although the model was designed for basic research in cognition, Martinez can foresee potential applications in the treatment of disorders that involve emotional triggers, such as PTSD, or a lack of recognition of other people’s emotions, such as autism.
“For example, if in PTSD people are more attuned to anger and fear, can we speculate that they will be tuned to all the compound emotions that involve anger or fear, and perhaps be super-tuned to something like ‘angrily fearful’? What are the pathways, the chemicals in the brain that activate those emotions? We can make more hypotheses now, and test them,” he said.
“Then eventually we can begin to understand these disorders much better, and develop therapies or medicine to alleviate them.”
The report is published in the journal Proceedings of the National Academy of Sciences.
Source: Ohio State University
Pedersen, T. (2018). New Computer Model Recognizes 21 Distinct Facial Expressions. Psych Central. Retrieved on September 30, 2020, from https://psychcentral.com/news/2014/04/12/new-computer-model-recognizes-21-distinct-facial-expressions/68438.html