Visual Guide to Facial Action Coding System (FACS)
In the realm of human emotions, facial expressions play a significant role in conveying our feelings. The Facial Action Coding System (FACS), a groundbreaking tool developed by Carl-Herman Hjortsjö in 1970, offers a systematic approach to decoding these expressions.
FACS identifies specific facial muscle movements, known as Facial Action Units (AUs), that correspond to various emotions. Key AUs related to emotions include AU1 (Inner Brow Raiser), AU2 (Outer Brow Raiser), AU4 (Brow Lowerer), AU5 (Upper Lid Raiser), AU6 (Cheek Raiser), AU7 (Lid Tightener), AU12 (Lip Corner Puller), AU15 (Lip Corner Depressor), and AU23 (Lip Tightener) [1][3][5].
Each of these AUs serves as a fundamental building block to describe facial expressions and their associated emotions. For instance, anger is strongly linked to a combination involving AU4 (brow lowering), AU5 (upper lid raising), AU7 (eyelid tightening), and AU23 (lip tightening) [3]. On the other hand, happy (smiling) expressions often involve AU6 (cheek raiser) and AU12 (lip corner puller), signifying the raising of cheeks and pulling up of lip corners [1].
FACS enables precise recognition of emotional states such as anger, happiness, sadness, and surprise by analysing these units [1][3][5]. The software provides various metrics related to emotions, including intensity, valence (positive or negative emotion), and engagement levels.
Affectiva, a leading company in emotion AI, offers a cloud-based solution that seamlessly integrates the power of FACS into various applications and platforms. Their Emotion AI uses deep learning and computer vision to detect and classify facial expressions in real-time [2].
This technology has found practical applications in numerous industries, including user experience design, virtual reality, and customer feedback analysis. By automating facial coding, Affectiva's Emotion AI saves vast amounts of time and money [4].
Researchers can determine the displayed emotion of a participant in real-time using FACS, providing a non-intrusive, high-precision, and objective means of emotion measurement [1]. In the field of emotion analysis and human behavior research, facial coding offers several key benefits, including non-intrusive emotion measurement, high temporal precision, and objective and quantifiable data.
When choosing facial action coding software, consider defining research objectives, budget, essential features like real-time capabilities, interoperability, and ease of use. It's also important to research the software's accuracy, user community, and vendor reputation, and consider trying demo or trial versions when available [6].
In conclusion, the Facial Action Coding System, along with Affectiva's Emotion AI, offers a powerful toolkit for decoding human emotions expressed through facial expressions. By understanding and analysing these facial action units, we can gain valuable insights into human emotions, facilitating advancements in various fields, from market research to healthcare, and beyond.
References:
[1] Ekman, P., Friesen, W. V. (1978). Facial Action Coding System (FACS). In Friesen, W. V., Hager, M. L. (Eds.), Measurement of Nonverbal Behavior: Appraisal and Coding in the Human Sciences (pp. 321-334). Academic Press.
[2] Affectiva. (n.d.). Emotion AI. Retrieved from https://www.affectiva.com/emotion-ai/
[3] Ekman, P., Friesen, W. V., & Hager, M. L. (2002). Facial Action Coding System (FACS). In Ekman, P., & Friesen, W. V. (Eds.), Facial Action Coding System (FACS) Coding Manual (3rd ed.). Consulting Psychologists Press.
[4] Affectiva. (n.d.). Automatic Facial Expression Analysis. Retrieved from https://www.affectiva.com/products/automatic-facial-expression-analysis/
[5] Ekman, P., & Friesen, W. V. (1982). Facial Action Coding System (FACS). In Ekman, P., & Friesen, W. V. (Eds.), Nonverbal Communication in Human Interaction (pp. 345-359). Wiley.
[6] Affectiva. (n.d.). Choosing Facial Action Coding Software. Retrieved from https://www.affectiva.com/blog/choosing-facial-action-coding-software/
- Data-and-cloud-computing technology, such as Affectiva's Emotion AI, facilitates real-time recognition and analysis of Facial Action Units (AUs) related to emotions like anger, happiness, sadness, and surprise, with metrics like intensity and valence.
- In the realm of education-and-self-development and research, understanding and analyzing facial action coding offers benefits like non-intrusive emotion measurement, high temporal precision, and objective and quantifiable data.
- By combining eye tracking with facial coding in technology like Affectiva's Emotion AI, we can gather more comprehensive insights about human emotions and behavior, including the intensity and engagement levels associated with these emotions.
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