Are there objective measures of facial symmetry used in smile analysis?

Okay, so I’m working on a project to try and automatically analyze smiles in photos and videos. I’m particularly interested in detecting genuine smiles versus forced ones. From what I’ve read, a key differentiator is the degree of symmetry – genuine smiles (Duchenne smiles) are supposed to be more symmetrical than fake smiles.

But "more symmetrical" is pretty subjective. I need to find objective, quantifiable ways to measure facial symmetry, specifically in the context of analyzing smiles. Are there existing tools, algorithms, or established methods used by researchers or in clinical settings (like orthodontics or plastic surgery) to measure things like:

• Horizontal symmetry of the lip corners (distance from the midline to each corner)?
• Vertical symmetry of the upper lip curvature?
• Eyebrow raising symmetry (how much each eyebrow raises during a smile)?
• Cheek raising symmetry (measuring the prominence of each cheek)?
• Asymmetry in the nasolabial folds (the lines running from the nose to the corners of the mouth)?

I’m not just looking for general image processing techniques; I’m interested in measures specifically relevant to facial features during a smile. I’ve found some papers mentioning things like "landmark-based morphometrics," but I’m hoping to find more concrete examples of how those landmarks are defined and the actual metrics used to calculate symmetry from them. Are there specific algorithms or software packages (even proprietary ones) that are typically used? Thanks!

Answer

Yes, there are objective measures of facial symmetry used in smile analysis. These measures utilize both manual and automated methods, often relying on digital imaging, 3D scanning, and computer-aided analysis to quantify facial features and their relationship to the midline. These methods aim to reduce subjectivity and provide more consistent and reliable assessments.

Horizontal Symmetry:

• Midline Assessment: A vertical line is drawn bisecting the face from the glabella (between the eyebrows) through the center of the upper and lower lip. Deviations of facial features from this midline are measured. These features include the nasal tip, philtrum (vertical groove between the nose and upper lip), and the center of the dental arch.

• Inter-Commissural Distance: The distance between the corners of the mouth (commissures) on each side of the face is measured. Differences in these distances can indicate asymmetry.

• Cheek Prominence: Assessment of the relative prominence of each cheek. This can be determined using 3D facial scans and analyzing the distances from the facial midline to the most prominent point on each cheek.

• Eye Position: Vertical and horizontal distances between specific landmarks of the eyes (e.g., inner and outer canthi) and the midline can also be compared.

Vertical Symmetry:

• Lip Height: Measurement of the vertical height of the upper and lower lip on each side of the face when smiling. Differences can indicate asymmetry in lip elevation.

• Gingival Display: Measurement of the amount of gingival (gum) tissue displayed above the upper teeth when smiling. Symmetry in gingival display is considered aesthetically pleasing. Excessive or uneven gingival display can be quantified.

• Tooth Display: Assessing the amount of tooth displayed, especially the incisal edges of the upper teeth, on either side of the midline when smiling. This includes tooth length, width, and inclination. Variations can indicate skeletal or dental asymmetries.

Angular Measurements:

• Lip Angles: Measurements of the angles formed by the lip lines with respect to the horizontal plane. Differences in these angles can indicate asymmetry in lip curvature.

• Commissure Angles: Measurement of the angle of the corners of the mouth during smiling. Different angles may indicate asymmetric muscle activation.

Methods and Technologies:

• Photography: Standardized facial photographs taken in a controlled environment are used for analysis. Specific facial landmarks are identified and measurements are taken using digital imaging software.

• 3D Facial Scanning: 3D scanners capture a detailed surface model of the face. This allows for precise measurements of distances, angles, and volumes, which can be used to assess symmetry.

• Computer-Aided Analysis: Specialized software is used to analyze digital images or 3D scans. These programs can automatically identify facial landmarks, calculate distances and angles, and provide quantitative measures of symmetry.

• Facial Action Coding System (FACS): While not directly a measure of symmetry, FACS can identify and quantify the activation of facial muscles during smiling. Analyzing the intensity and coordination of muscle activation on each side of the face can reveal asymmetries in facial expression.

Specific Indices and Ratios:

• Franckfort Horizontal Plane: A reference plane defined by the lowest point on the margin of the bony orbit (porion) and the highest point on the infraorbital margin (orbitale). Facial features are often analyzed in relation to this plane to assess vertical symmetry and alignment.

• Facial Proportions: Ratios between various facial measurements, such as nose width to face width or lip height to lower face height, are compared to established norms to assess facial balance and symmetry.

Limitations:

• Ideal Symmetry is Rare: Complete facial symmetry is uncommon in humans. Therefore, the goal is often to identify and address significant asymmetries that detract from the overall aesthetic appearance of the smile.

• Static vs. Dynamic Assessment: Many objective measures focus on static facial features. However, dynamic symmetry (symmetry during facial movement) is also important. FACS and video analysis can help assess dynamic symmetry.

• Ethnic and Individual Variations: Facial proportions and symmetry vary among different ethnic groups and individuals. Normative data should be appropriate for the individual being assessed.

• Soft Tissue Considerations: Assessing only hard tissue structures (bone and teeth) provides incomplete information. Soft tissue structures (lips, cheeks) also contribute to facial symmetry and smile aesthetics.

In conclusion, while perfect facial symmetry is rare, objective measures provide a means to quantify and analyze facial features in order to assess symmetry in smile analysis. These measurements, obtained through photographs, 3D scans, and software, are used to evaluate horizontal, vertical, and angular symmetry, improving the accuracy and reliability of smile assessment.