Identify people's psychology through facial expressions.

Identify people's psychology through facial expressions.

There is a way to recognize people's psychology through facial expressions. In life, there is a way to know what a person is thinking. We can identify people's psychological changes through their facial expressions. So do you know how to recognize people's psychology through facial expressions? Come and have a look with me!

Identifying people's psychology through facial expressions 1 In people's daily communication, only 7% of information is transmitted through language, and 55% of information is reflected through facial expressions. Obviously, the importance of expression information in interpersonal communication.

With the continuous development of artificial intelligence and pattern recognition, facial expression recognition, an important technology in human-computer intelligent interaction, has also attracted much attention. Facial expression recognition mainly uses facial recognition technology to extract and classify facial expression information, so that computers can know people's expression information, and then infer people's psychological state, thus realizing advanced intelligent interaction between human and computer.

From the recognition mode, facial expression recognition is consistent with our behavioral psychology. There is a saying in behavioral psychology that the super psychological password for instantly recognizing people is to look at each other's faces for the first time. Judging a person's mental state through expression means observing the other person's mind through tiny expressions and tiny movements, and making accurate inferences about what will happen.

At present, the application fields of facial expression recognition are mainly security field, intelligent robot development, computer games, medical field and so on. Facial expression recognition mainly defines six expressions: anger, disgust, fear, sadness, joy and surprise, and divides the face into several movement units to describe facial movements, which show the corresponding relationship between facial movements and expressions.

Facial expression recognition can be divided into three parts: face image acquisition and preprocessing, expression feature extraction and expression classification. It is basically consistent with face recognition in the acquisition and preprocessing of face images, but it is different in feature extraction. The feature extracted by face recognition is the individual difference of the same face, while the feature extracted by expression recognition is the difference of the same face with different expressions.

Identifying people's psychology through facial expressions 2 Aristotle said that the face is the window of the soul, and a person's thoughts can be seen through expressions. Cicero, a great philosopher in ancient Rome, is also a supporter of this view. Indeed, two thousand years later, regardless of age, gender and cultural differences, facial expressions are still widely regarded as an effective way to judge people's feelings. For example, raising eyebrows means confusion, smiling means happiness and frowning means sadness.

But is this really the case? Psychologists have analyzed hundreds of papers on the relationship between facial expressions and potential emotions, and the conclusion is somewhat surprising: there is no detailed scientific evidence that people's daily emotions can be recognized by facial expressions. In other words, just because a person doesn't laugh doesn't mean he is unhappy.

Psychologists have found that adults living in cities are 30% more likely to frown when they are angry. This means that people don't frown about 70% of the time when they are angry. On the contrary, people use frowning in other places, for example, when people concentrate, when someone tells a bad joke, or when they are angry inside (when they want to fart).

The researchers concluded that frowning or frowning is one of the ways people express their anger, but it is by no means the only way. The complexity and unpredictability of human facial expressions are not limited to anger, but also apply to six emotional categories defined by psychologists: anger, disgust, fear, happiness, sadness and surprise.

This makes people question the efforts of technology companies to develop artificial intelligence algorithms. Technology companies always claim that artificial intelligence algorithms can recognize facial expressions and calculate potential emotional states. For example, Microsoft claims that its "sentiment analysis application" can judge people's inner feelings by detecting their video clips. However, Alex Martinez, a computer engineer at Ohio State University, is skeptical. He believes that trying to identify human emotions based on face images actually ignores the importance of the background environment that produces emotions.

First of all, facial expression is one of many nonverbal forms that people use to communicate, and so is body language. Artificial intelligence also needs to consider these factors to identify people's emotions. For the interpretation of facial expressions, it seems more important to understand the emotional background. Dr Martinez cited an experiment to prove this point. In this experiment, the researchers showed participants a close-up photo of a man's face, in which his mouth was wide open, as if he were screaming and his face was red.

Based on this, most participants will guess that the people in the photo are very angry. However, when you pull the photo to the panorama, you find that the photo is actually a football player holding out his arms to celebrate the goal. His face, which partly looks like an angry face, is actually an ecstatic expression.

Considering that people can't accurately guess each other's emotional state through expressions most of the time, Dr. Martinez believes that computers can't do this either. He said: "Some companies claim that algorithms can identify people's emotional state through their expressions and apply them to recruitment and other scenarios." "Some companies require candidates to submit video resumes, and then analyze their facial expressions through machine learning systems, and then draw conclusions about whether they are suitable for employment. This is really shocking, because some algorithms may be based on wrong assumptions, or even a dangerous assumption, and the conclusions drawn on this basis may be very terrible.