1. As applied to face recognition

3.  Detection vs. Recognition

4.  Identification vs. Verification

5.  Components:  Face Detection  Face Alignment  Feature Extraction  Matching

6.  Components:  Face Detection  Face Alignment  Feature Extraction  Matching

8.  Dimensionality Reduction

9.  “Eigenface” analysis

10. Unordered Observations LightTemp. 2.52.4 0.50.7 2.22.9 1.92.2 3.13 2.32.7 21.6 11.1 1.51.6 1.10.9

13.  Turns 4096 dimensions -> 40 or less dimensions

14. 1.811.91 2.52.4 0.50.7 2.22.9 1.92.2 3.13 2.32.7 21.6 11.1 1.51.6 1.10.9

15. 1.811.91 2.52.4 0.50.7 2.22.9 1.92.2 3.13 2.32.7 21.6 11.1 1.51.6 1.10.9 0.690.49 -1.31-1.21 0.390.99 0.090.29 1.291.09 0.490.79 0.19-0.31 -0.81 -0.31 -0.71-1.01

17. 0.690.49 -1.31-1.21 0.390.99 0.090.29 1.291.09 0.490.79 0.19-0.31 -0.81 -0.31 -0.71-1.01.69-1.31.39.091.29.49.19-.81-.31-.71.49-1.21.99.291.09.79-.31-.81-.31-1.01

18. .69-1.31.39.091.29.49.19-.81-.31-.71.49-1.21.99.291.09.79-.31-.81-.31-1.01 0.616555560.61544444 0.71655556

19. 0.04908341.28402771 -.73517866-0.6778734 0.6778734-0.73517866 Eigenvalues Eigenvector 1Eigenvector 2

20.  “Characteristic”

21.  Vector characterizing a feature of the matrix

22.  “Characteristic”  Vector characterizing a feature of the matrix  Eigenvalue = strength

23. -.73517866-0.6778734 0.6778734-0.73517866 Eigenvalues Eigenvector 1Eigenvector 2 0.04908341.28402771

25. -.73517866-0.6778734 0.6778734-0.73517866 -.73517866 0.6778734 -0.6778734-0.73517866.69-1.31.39.091.29.49.19-.81-.31-.71.49-1.21.99.291.09.79-.31-.81-.31-1.01

26. -.828 1.78 -.992 -.27 -1.67 -.912.099 1.144.438 1.22 2.52.4 0.50.7 2.22.9 1.92.2 3.13 2.32.7 21.6 11.1 1.51.6 1.10.9

29.  [0,0,0,127, 55, 234, 255, 123, 98… n]  n = width * height

30. Image1 Image2 Image3 Image4 000127552342551239865 23156712576209132649222 762342009811o85145974432 209539919839201382207792

31. Average

32. 000127552342551239865 23156712576209132649222 762342009811o85145974432 209539919839201382207792 -77-75.5-91.5-10-1.6751.75112.5-320.2512.25 -54-60.5-24.5-1219.326.75-10.5-6214.25-30.75 158.5108.5-3953.3-97.252.5-29-33.75-20.75 132-22.57.561-17.6718.75-104.594-0.7539.25 7775.591.513756.67182.3142.512677.7552.75

34. Eigenvalues Eigenvectors.00006450.9784.828173.8213.018 -.24-.05-.17.13.33 -.24-.001-.034.462.317 -.24-.367-.1.006.134 -.24-.222.412.082-.308 -.24.0008.048-.057.192 Principal component

37.  Animation of reconstruction Animation of reconstruction

38. .5.2.1.03.005

39.  Demo