Attention is a cognitive process that tells us about somebody’s concentration and ability to actively process specific information. It's based on a methodology developed by a group of scientists from SWPS and Clemson University that succeeded in creating a K-coefficient. This parameter uses eye movement parameters (fixation duration and saccade amplitude) to define the path of attention dynamic of an examined person. Facial Coding allows you to track the emotions on the participants' faces. It's based on a methodology developed by Carl-Herman Hjortsjö and adopted in 1972 by Paul Ekman and Wallace V. Friesen for interpreting emotional states by facial muscle movements (FACS). Now, computer vision supported with AI algorithms allows us to analyze people's emotions online.
There were many attempts to create a dynamic visual attention indicator. Finally a group of scientists from SWPS and Clemson University (who we had the pleasure to meet and work with) succeeded in creating a K-coefficient. This parameter uses eye movement parameters (fixation duration and saccade amplitude) to define the path of attention dynamic of an examined person.
In eye-tracking research, we can distinguish two general types of visual attention: ambient and focal. Ambient attention indicates a scanning pattern over stimuli (typical for the early stages of scene perception), characterized by short duration fixations followed by long saccades. On the other hand, longer fixations followed by shorter saccades indicate focal attention. The more focal processing of the stimuli, the deeper attention is given, which can mean that someone is actively processing the information.
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In eye-tracking research, we can distinguish two general types of visual attention: ambient and focal. Ambient attention indicates a scanning pattern over stimuli (typical for the early stages of scene perception), characterized by short duration fixations followed by long saccades. (...)
Learn More...The Facial Action Coding System (FACS) is a system that allows the quantification and measurement of facial movements. It was initially developed by a Swedish anatomist - Carl-Herman Hjortsjö, and adopted by Paul Ekman and Wallace V. Friesen in 1978. Ekman and Friesen later updated the system in 2002. (...)
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Facial coding is a process that quantifies emotional responses to digital content. It's deeply rooted in Paul Ekman's research, uses software and webcam capture to interpret complex human emotions through facial expressions. Dr. Ekman's research has identified six basic emotional expressions that are universally recognized across cultures.
These expressions are:
And they are distinguished by different facial muscle movements. This highlights the universality of emotions through facial expressions, making facial coding technology an important tool in market research all over the world.
In 1978, Ekman and Friesen released the Facial Action Coding System (FACS), which maps the movements of facial muscles. Facial Action Coding System decays the facial behavior into 46 so-called action units. What are precisely action units? As we wrote in previous article „They are defined as contractions or relaxations of one or more facial muscles. The FACS manual has over 500 pages and describes all action units along with their meaning according to Ekman’s interpretation”.
The Facial Action Coding System has changed how emotional responses are interpreted. This approach has improved the accuracy of facial coding, making it a great technique for ad and video testing among research and advertisement agencies. By tapping into consumers' emotional responses, researchers can gain deeper insights into how people react to stimuli. This, in turn, enables companies and agencies to create more effective marketing campaigns and products that resonate with their target audience.
The science behind facial coding is relatively simple. It records facial expressions via webcam and analyzes them using facial coding software.
The process of face coding typically involves these steps:
Face coding is often used with other research methods, such as surveys or eye-tracking. It provides insights into user experience, marketing, and product development strategies.
Facial coding has revolutionized the way we understand basic emotions. This amazing research tool can be used in many industries.
Automated facial coding is very popular in marketing and consumer research. Marketers love face coding! They use trackers like RealEye to measure emotional responses to their campaigns. This research technique provides moment-by-moment emotional and cognitive metrics, allowing for optimized marketing strategies and more effective ad campaigns.
Facial coding can also help with your market research. One effective way to gather insights into customers' feelings about your products is to conduct market research using face coding. This can help you find areas for improvement and make adjustments before your products hit the store shelves. You can also proactively handle any negative feedback that may come your way.
That’s a great question! If you need a TLDR type of answer, it’s a short: no. The terms „face coding” and „face recognition” are related concepts but serve different purposes.
The coding process typically doesn't involve identifying specific individuals but focuses on interpreting basic emotions and reactions based on facial expressions. It also utilizes the previously mentioned Facial Action Coding System (FACS) to categorize and analyze facial movements.
Face recognition, on the other hand, was created to verify individuals' identities based on their facial features. It's a process that involves comparing a person's face with a database of known faces to see if there's a match. It has applications, e.g., in security systems, access control, law enforcement, and digital authentication.
You already know a lot about face coding and its use on the market. What are the top strengths of this tool?
It's exciting to see how facial coding changes how technology interacts with human emotions.
Emotion AI Integration: In 2018, Gartner's Top Predictions Report predicted that by 2022, 10% of devices would possess emotion AI capabilities. In 2019, Gartner further predicted that by 2024, AI's ability to identify emotions would seriously impact over half of the online advertisements users experience.
Transformational Impact: When used ethically, facial coding possesses the remarkable ability to improve consumer interactions, redefine entire industries, and positively impact people's lives.
Ethical Issue: As more companies use facial coding, it's important to manage issues around privacy and consent. Responsible implementation and transparency are essential for the benefit of everyone involved.
The world is in a constant change, and technology never stops to amaze us. To keep up with the competition, it is wise to use the latest tools and metrics that the market offers. Facial coding can help businesses recognize emotions, but many are unaware of its importance.
Experience the power of Face coding and take your content to the next level!
