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Analysis of the Human Face

Analysis of the Human Face. 9/12/06. 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. Fibonacci numbers.

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Analysis of the Human Face

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

  2. 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

  3. 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 1.618 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, …

  4. 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

  5. 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.

  6. Other Parameters? • Shadow • Skin Reflectance • Emotion? • Others?

  7. 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

  8. 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

  9. 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?

  10. 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)

  11. 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.

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