A computer system is able to spot fake facial expressions better than humans can.
"The computer system managed to detect distinctive dynamic features of facial expressions that people missed," Marian Bartlett, research professor at UC San Diego's Institute for Neural Computation and lead author of the study said in a University of Toronto news release. "Human observers just aren't very good at telling real from faked expressions of pain."
"Humans can simulate facial expressions and fake emotions well enough to deceive most observers. The computer's pattern-recognition abilities prove better at telling whether pain is real or faked," senior author Kang Lee, professor at the Dr. Eric Jackman Institute of Child Study at the University of Toronto said in the news release.
The team found that humans could not determine if a facial expression was real or fake better than random chance. After being trained to recognize faked facial expressions of pain the participants were only able to distinguish between the two with an accuracy of 55 percent.
"In highly social species such as humans," said Lee, "faces have evolved to convey rich information, including expressions of emotion and pain. And, because of the way our brains are built, people can simulate emotions they're not actually experiencing - so successfully that they fool other people. The computer is much better at spotting the subtle differences between involuntary and voluntary facial movements," Lee said.
The most prevalent "feature of falsified expression" is the opening of the mouth. People who are faking pain tend to open and close their mouth in a regular pattern. The researchers hope this new computer system will be able to determine other deceptive actions and be used for applications such as homeland security, job screening, and psychopathology.
"As with causes of pain, these scenarios also generate strong emotions, along with attempts to minimize, mask, and fake such emotions, which may involve 'dual control' of the face," she said. "In addition, our computer-vision system can be applied to detect states in which the human face may provide important clues as to health, physiology, emotion, or thought, such as drivers' expressions of sleepiness, students' expressions of attention and comprehension of lectures, or responses to treatment of affective disorders."
