What is Facial Expression Recognition?
Facial expression recognition software is a technology which uses biometric markers to detect emotions in human faces. More precisely, this technology is a sentiment analysis tool and is able to automatically detect the six basic or universal expressions: happiness, sadness, anger, surprise, fear, and disgust.
Why is Facial Expression Recognition important?
Facial expression recognition or computer-based facial expression recognition system is important because of its ability to mimic human coding skills. Facial expressions and other gestures convey nonverbal communication cues that play an important role in interpersonal relations. These cues complement speech by helping the listener to interpret the intended meaning of spoken words. Therefore, facial expression recognition, because it extracts and analyzes information from an image or video feed, it is able to deliver unfiltered, unbiased emotional responses as data.
How does Facial Expression Recognition work?
Facial expression recognition system is a computer-based technology and therefore, it uses algorithms to instantaneously detect faces, code facial expressions, and recognize emotional states. It does this by analyzing faces in images or video through computer powered cameras embedded in laptops, mobile phones, and digital signage systems, or cameras that are mounted onto computer screens. Facial analysis through computer powered cameras generally follows three steps:
1. Face detection
Locating faces in the scene, in an image or video footage.
2. Facial landmark detection
Extracting information about facial features from detected faces. For example, detecting the shape of facial components or describing the texture of the skin in a facial area.
3. Facial expression and emotion classification
Analyzing the movement of facial features and/or changes in the appearance of facial features and classifying this information into expression-interpretative categories such as facial muscle activations like smile or frown; emotion categories happiness or anger; attitude categories like (dis)liking or ambivalence.
How can Facial Expression Recognition software be used?
For businesses, since facial expression recognition software delivers raw emotional responses, it can provide valuable information about the sentiment of a target audience towards a marketing message, product or brand. It is the most ideal way to assess the effectiveness of any business content.
There are several ways that facial expression recognition software can be used by businesses. Here are two examples:
Companies have traditionally done market research by conducting surveys to find out about what consumers want and need. This method however, assumes that the preferences stated are correct and reflect future actions. But this is not always the case. Another popular approach in market research is to employ behavioral methods where user’s reactions are observed, while interacting with a brand or a product. Although effective, such techniques can quickly become very labor intensive as the sample size increases. In such circumstances, facial expression recognition technology can save the day by allowing companies to conduct market research and measure moment-by-moment facial expressions of emotions automatically, making it easy aggregate the results.
Video game testing
Facial expression recognition can also be used in the video game testing phase. In this phase, usually a focus group of users is asked to play a game for a given amount of time and their behavior and emotions are monitored. By using facial expression recognition, game developers can gain insights and draw conclusions about the emotions experienced during game play and incorporate that feedback in the making of the final product.
Facial expression analysis is a practical means of going beyond the typical survey approach. It is a way of appreciating what the user is experiencing, all while getting feedback. When feedback is taken in this format, it becomes genuinely non-intrusive when it comes to user experience.