Facial Symmetry Analysis

1. Jason Mak Facial Symmetry Analysis

2. Project Statement and Motivation • The goal of this project is to automatically detect the facial symmetry axis and measure the symmetry of a given face. • The purpose of this project is to create a form of biometric data, which could be useful for various detection processing or medical analysis.

3. Project Approach • 1.)Skin Detection • Use a Gaussian distribution of chroma (YCbCr) values from a collection of skin samples, to detect possible skin candidates • Apply an adaptive threshold to create a binary image of the skin region • 2.)Symmetry Axis Determination • Use the binary image to determine the center of mass • From the center of mass, crop out face region to remove noise • 3.)Gray Level Difference Calculation • Compare the right side values to the left side values correspondingly, pixel by pixel • 4.) Misalignment Adjustment • Shift symmetry axis and compare gray level difference, in case symmetry axis is misaligned

4. Results – Symmetric

5. Results – Symmetric (cont’d)

6. Results – Less Symmetric

7. Results - Extremes

8. Results – Errors

9. Results – Errors

10. Difficulties and Future Work • Skin detection was a difficulty because of the small range in the database I chose. Improvement would come with a more thorough database of skin samples and a more accurate Gaussian distribution. • Symmetry axis determination was a difficulty because of the slight variations that came with each image. Although I was able to deal with misaligned axis, I could not account for images with tilted faces. • Skin detection was also a difficulty because lighting would effect the detection, causing skin regions to be neglected and non-skin regions to be accepted. Being able to account for lighting and texture differences would greatly improve such problems.

11. End