1. Analysis of the Human Face
9/12/06

3. What are the Parameters?
Length of Ear
Interpupillary Distance
Length of face
Width of face
2 measurements (ear to nose, both sides)
Length of nose

4. Fibonacci numbers
Fibonacci numbers are defined as a number which when divided by the number in the sequence before it, yields a number close to 1.618
fixed at precisely after the 13th in the series.
known as the "golden ratio."
0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610, 987, 1597, 2584, …

5. GOLDEN RATIO = 1.618
233 / 144 = 1.618
377 / 233 = 1.618
610 / 377 = 1.618
987 / 610 = 1.618
1597 / 987 = 1.618
2584 / 1597 = 1.618
L. Pisano Fibonacci

6. The Golden Ratio in the Human Face
There are several golden ratios in the human face.
refers to the "ideal human face" determined by scientists and artists.
The total width of the two upper front teeth /their height
Length of face / width of face,
Distance between the lips and where the eyebrows meet /length of nose
Length of face / distance between tip of jaw and where the eyebrows meet
Length of mouth / width of nose
Width of nose / distance between nostrils,
Distance between pupils / distance between eyebrows.

8. Other Parameters?
Shadow
Skin Reflectance
Emotion?
Others?

9. Data Collection
Once we agree on measurements to be taken, each student will be assigned a number, will take face diagrams and a ruler.
The class will be divided into two groups at random
Each group will measure the facial parameters of the members of the other group and record the data on the face diagrams
This will provide multiple measurements on each subject

10. How will we analyze the data?
Measurements for each subject will be entered into an Excel spreadsheet and used to calculate:
Mean, deviation, variance and standard deviation
Data will be combined to analyze
Group 1 vs. group 2
Male vs female
Other groupings?
Differences between groups will be analyzed for significance using the student’s t test

11. What does the analysis mean?
Have we introduced any biases into our measurement?
Is what we have done an “experiment”?
What conclusions can be drawn from our measurements? Can we extrapolate to the general population?
What would you do to improve the quality and/or significance of the data?

12. How facial data are used
The analysis of the model parameters for sample populations has revealed variations according to subject age, gender, skin type, and external factors (e.g., sweat, cold, or makeup).
Users can edit the overall appearance of a face (e.g., changing skin type and age) or change small-scale features using texture synthesis (e.g., adding moles and freckles)
Currently under intense development for counter-terrorism (face recognition)

13. For Next Time
Please read Chapter 10 (page 145) in “The Art of Science”.
For extra credit:
Obtain data from the internet or other source on facial data from another population
E.g., distance between eyes as a function of gender, age, etc.