Master the Art of Facial Expressions: The Ultimate FACS Guide Revealed!

Facial expressions are a powerful and universal form of communication, conveying emotions and intentions without the need for words. Understanding and interpreting these expressions is crucial in various fields, including psychology, marketing, animation, and human-computer interaction. The Facial Action Coding System (FACS) provides a standardized method for analyzing and categorizing facial expressions based on the underlying muscle movements. This article delves into the intricacies of FACS, its applications, and how it can be utilized effectively.

Introduction to the Facial Action Coding System (FACS)

The Facial Action Coding System (FACS) is a comprehensive system for describing and classifying facial expressions based on the specific muscle movements that produce them. Originally developed by Carl-Herman Hjortsjö in 1970 with 23 facial motion units, it was later refined and expanded by Paul Ekman and Wallace Friesen. FACS serves as a "visual guidebook", showcasing the power of facial action and providing a valuable reference point. By identifying and coding these "action units" (AUs), researchers and practitioners can objectively analyze and interpret facial expressions, gaining insights into a person's emotional state, intentions, and underlying cognitive processes.

The Significance of FACS

FACS offers several advantages over other methods of emotion measurement:

Non-Intrusive Emotion Measurement: Facial coding allows for non-intrusive and natural emotion measurement, as it captures emotional expressions in real time without requiring participants to report their feelings verbally or in writing.
High Temporal Precision: Facial coding provides high temporal precision, enabling researchers to analyze micro-expressions and subtle changes in facial expressions, which may occur in fractions of a second.
Objective and Quantifiable Data: Facial coding generates objective and quantifiable data, making it suitable for both research and commercial applications.

The Building Blocks of FACS: Action Units (AUs)

At the core of FACS are Action Units (AUs), which represent the fundamental muscle movements that create facial expressions. Each AU corresponds to the contraction of one or more facial muscles. By identifying which AUs are present in a facial expression, it is possible to determine the underlying emotional state.

Major Action Units and Their Corresponding Muscle Movements

Here are some of the major action units used to determine emotions:

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AU1: Inner Brow Raiser (Frontalis, pars medialis)
AU2: Outer Brow Raiser (Frontalis, pars lateralis)
AU4: Brow Lowerer (Corrugator supercilii, Depressor supercilii, Procerus) knits (corrugator supercilii) and lowers (procerus, depressor supercilii, and parts of corrugator supercilii) the brow area and lower central forehead.
AU5: Upper Lid Raiser (Levator palpebrae superioris)
AU6: Cheek Raiser (Orbicularis oculi, pars orbitalis)
AU7: Lid Tightener (Orbicularis oculi, pars palpebralis) NOTE: The pretarsal area is the portion of our orbicularis oculi muscle that is involved with blinking.
AU8: Lips toward each other brings the upper and lower lips toward each other by lowering the top lip and raising the bottom lip. Lips toward each other functions as a way to bring the lips back together from actions that may separate the lips.
AU9: Nose Wrinkler (Levator labii superioris alaeque nasi) NOTE: The brow lowering you see in nose wrinkler is not directly caused by the levator labii superioris alaeque nasi (LLSAN) muscle. Rather, it is caused by the brow lowering muscles often paired with nose wrinkler: depressor supercilii and procerus.
AU10: Upper Lip Raiser (Levator labii superioris)
AU11: Nasolabial Deepener (Zygomaticus minor)
AU12: Lip Corner Puller (Zygomaticus major)
AU13: Cheek Puffer (Buccinator)
AU14: Dimpler (Buccinator)
AU15: Lip Corner Depressor (Depressor anguli oris)
AU16: Lower Lip Depressor (Depressor labii inferioris)
AU17: Chin Raiser (Mentalis) NOTE 1: AU17 - chin raiser appears during the in-between steps.
AU18: Lip Pucker (Orbicularis oris, Incisivus labii superioris, Incisivus labii inferioris) NOTE 1: Incisivus labii superioris and incisivus labii inferioris are considered accessory muscles to orbicularis oris.NOTE 2: Lip pucker typically co-activates vertical lip tightener (as seen in this example).
AU20: Lip Stretcher (Risorius) NOTE1: Not to be confused with mouth stretch. NOTE2: Risorius is one of the most variable facial muscles in humans.
AU21: Neck Tightener
AU22: Lip Funneler (Orbicularis oris)
AU23 (horizontal type): Lip Tightener thins the lips. NOTE: This 2-type distinction is a deviation from official FACS. Only “horizontal type” qualifies as lip tightener in original FACS.
AU24: Lip Presser (Orbicularis oris) NOTE: You may see lip presser spelled as “lip pressor” in many sources.
AU25: Lips Part NOTE: In FACS, AU25 - lips part, refers to the state of the lips being parted. This parting can be caused by any action that separates the lips
AU26: Jaw Drop (Masseter, Temporalis, Pterygoids) In the above reference, AU26 - jaw drop is the cause of separated lips, and AU8 is used to close the lips while allowing the jaw to remain open.
AU27: Mouth Stretch forcefully lowers the lower mandible (jaw). NOTE: Because the word “mouth” is quite ambiguous and can colloquially refer to either the lips and/or jaw, mouth stretch can be easily confused with similarly-named actions like lip stretcher.

Combining Action Units to Identify Emotions

Certain combinations of AUs are associated with specific emotions. For example, happiness is typically characterized by the combination of AU6 (cheek raiser) and AU12 (lip corner puller). Emotion recognition systems, such as Affectiva Emotion AI integrated into iMotions, utilize these combinations to identify the emotions being displayed.

Applications of FACS

FACS has a wide range of applications across various fields:

Research

Psychology: FACS is used to study the relationship between facial expressions and emotions, providing insights into the neural mechanisms underlying emotional processing.
Social Sciences: Researchers use FACS to investigate social interactions, communication patterns, and the role of emotions in social behavior.
Human-Computer Interaction: FACS is employed to develop more natural and intuitive interfaces that can recognize and respond to users' emotional states.

Commercial Applications

Market Research: FACS is used to gauge consumer reactions to products, advertisements, and other marketing stimuli, providing valuable feedback for improving marketing strategies.
Entertainment: Animators and game developers use FACS to create realistic and expressive characters, enhancing the immersive experience for viewers and players.
Healthcare: FACS is used to monitor patients' emotional states, assess pain levels, and detect early signs of mental health conditions.

Real-Time Emotion Recognition

Facial coding can be used for real-time emotion recognition in applications such as human-computer interaction, market research, and affective computing. Advances in computer vision and facial recognition technology have enabled the development of real-time facial coding systems that can analyze facial expressions as they occur. These systems use machine learning algorithms to detect and classify emotions based on the movements and patterns of facial muscles in real-time video streams.

Choosing the Right Facial Action Coding Software

Selecting the appropriate facial action coding software is crucial for accurate and efficient analysis. Consider the following factors when making your decision:

Research Objectives and Budget: Define your research goals and budget to narrow down your options.
Essential Features: Assess essential features like real-time capabilities, interoperability, and ease of use.
Accuracy: Research the software's accuracy and validation studies.
User Community and Vendor Reputation: Look for software with a strong user community and a reputable vendor.
Demo or Trial Versions: Take advantage of demo or trial versions to test the software before committing to a purchase.

Affectiva Emotion AI

Integrated into iMotions is the Affectiva Emotion AI, which is a highly specialized emotion recognition technology. The Emotion AI platform is designed for understanding and analyzing human emotions from facial expressions.

Emotion Recognition: Affectiva’s Emotion AI uses deep learning and computer vision to detect and classify facial expressions in real-time.
Emotion Metrics: The software provides various metrics related to emotions, including intensity, valence (positive or negative emotion), and engagement levels.

The FACS Cheat Sheet and Beyond

The FACS Cheat Sheet is a visual guide for the Facial Action Coding System (FACS) and beyond. Here you will find FACS-based action unit (AU) references and the facial muscles they map to. This guide is designed for animators, modelers, riggers, sculptors, and researchers interested in FACS and facial anatomy.

Non-FACS Movements

Due to FACS’s original purpose as a facial behavior identification system, FACS lacks documentation for some finer, more nuanced facial movements. To fill this void, nonFACS movements are defined such as: vertical lip tightener, y-axis dimpler, open-eye blink, etc.

Auricular Muscles

NOTE 2: There are multiple auricular muscles. The superior auricular moves the ears up. The posterior auricular moves the ears back. The anterior auricular the moves ears forward. At present, these movements cannot be separated.

Wink

NOTE: Unless you are a facial coder conducting behavioral research (and even then, the official FACS Manual lists AU46 - wink as “optional”), the FACS shape for wink is not the most useful.

Lip Tightener

NOTE: This 2-type distinction is a deviation from official FACS. Only “horizontal type” qualifies as lip tightener in original FACS. I have chosen to divide lip tightener into two types, because the lips tighten in distinct manners. The muscle behind both movements, orbicularis oris, possesses rich variation in fiber directionality; such directional variation yields more potential actions for orbicularis oris than have thus far been documented. The distinction of horizontal vs. vertical lip tightening proves especially useful when breaking down speech.

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Lip Presser

NOTE: You may see lip presser spelled as “lip pressor” in many sources.

Mouth Stretch

NOTE: Because the word “mouth” is quite ambiguous and can colloquially refer to either the lips and/or jaw, mouth stretch can be easily confused with similarly-named actions like lip stretcher.

Tips for Drawing Facial Expressions

The relationship between the EYE & EYEBROWS is very important. When the two are combined really well it can solve half the equation of drawing CLEAR and ACCURATE facial expressions of your character.
The meaning and intensity of a character's facial expression can completely change just by adjusting the angle and tilt of the head via the neck.

Improving Writing with Facial Expression Descriptions

Facial expression descriptions in writing help the readers picture the characters and to convey emotions. However, it’s easy to rely on the same descriptions over and over again. The expressions are broken down by the part of the face. Note that some of them work for more than one emotion-a person might narrow their eyes out of vindictiveness or skepticism, for instance, and their face might turn red out of anger or out of embarrassment. Some of them require a little more explanation on your part. You’ll have to say what she’s glaring at, or if his face is contorting in rage, or grief, or what. And not all of these will work for every character. In many cases I’ve given several ways to describe the same thing. Some of these aren’t exactly words to describe facial expressions, but they’re useful for dialogue tags.

Accuracy and Training

The accuracy of FACS is highly dependent on the training and expertise of the individuals using it. When administered by experienced FACS coders under controlled conditions, FACS can achieve a high level of accuracy in coding facial expressions. Training is highly recommended and typically encouraged to use the Facial Action Coding System (FACS) effectively at a high level.

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