At face value

Talk about taking your work home with you — whenever Yan Tong has a conversation with someone or watches a movie, she finds herself making mental note of everyone's facial expressions.

That's because her research on affective computing involves cataloging facial expressions with the goal of programming computers to recognize certain emotions.

"This is a grand challenge task," said Tong, a computer science faculty member at the University of South Carolina whose expertise has led to her invitation to review papers from 14 top journals and at seven international conferences. "If we are successful, computers could be used to recognize signs of road rage or intoxication in automobile drivers or to help teach autistic children how to interpret and respond appropriately to facial cues."

Previous researchers in affective computing have determined that facial expressions associated with happiness, anger, fear, sadness, disgust and surprise are largely the same across cultures and nationalities. Labels have been assigned to the spectrum of facial expressions associated with those emotions, then programmed into computers.

"Imagine an online instructor who is teaching hundreds of students at the same time and doesn't notice that a bunch of students look bored or puzzled," she said. "A computer could spot the facial expressions and alert the instructor who might then speed up or slow down the pace of the lecture."

Humans can readily perceive even subtle facial expressions when interacting with others, partly because having two eyes results in stereo vision and mobility allows someone to move closer or further away. A computer has neither of those capabilities, making the task of programming even more difficult.

"Human emotion is very subtle; the difference between a social smile and a smirk can be very small," said Tong, the recipient of a CAREER Award from the National Science Foundation. "A computer has a difficult time figuring out what kind of smile it is seeing. That's the challenge of our work."

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