Principal Components Analysis
description
Transcript of Principal Components Analysis
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As applied to face recognition
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Detection vs. Recognition
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Identification vs. Verification
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Components: Face Detection Face Alignment Feature Extraction Matching
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Components: Face Detection Face Alignment Feature Extraction Matching
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Dimensionality Reduction
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“Eigenface” analysis
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Unordered Observations
LightTemp.
2.5 2.4
0.5 0.7
2.2 2.9
1.9 2.2
3.1 3
2.3 2.7
2 1.6
1 1.1
1.5 1.6
1.1 0.9
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Turns 4096 dimensions -> 40 or less dimensions
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1.81 1.91
2.5 2.4
0.5 0.7
2.2 2.9
1.9 2.2
3.1 3
2.3 2.7
2 1.6
1 1.1
1.5 1.6
1.1 0.9
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1.81 1.91
2.5 2.4
0.5 0.7
2.2 2.9
1.9 2.2
3.1 3
2.3 2.7
2 1.6
1 1.1
1.5 1.6
1.1 0.9
0.69 0.49
-1.31 -1.21
0.39 0.99
0.09 0.29
1.29 1.09
0.49 0.79
0.19 -0.31
-0.81 -0.81
-0.31 -0.31
-0.71 -1.01
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0.69 0.49
-1.31 -1.21
0.39 0.99
0.09 0.29
1.29 1.09
0.49 0.79
0.19 -0.31
-0.81 -0.81
-0.31 -0.31
-0.71 -1.01
.69 -1.31
.39 .09 1.29
.49 .19 -.81 -.31 -.71
.49 -1.21
.99 .29 1.09
.79 -.31 -.81 -.31 -1.01
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.69 -1.31
.39 .09 1.29
.49 .19 -.81 -.31 -.71
.49 -1.21
.99 .29 1.09
.79 -.31 -.81 -.31 -1.01
0.61655556 0.61544444
0.61544444 0.71655556
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0.0490834 1.28402771
-.73517866 -0.6778734
0.6778734 -0.73517866
EigenvaluesEigenvector 1 Eigenvector 2
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“Characteristic”
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“Characteristic”Vector characterizing a feature of
the matrix
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“Characteristic”Vector characterizing a feature of
the matrixEigenvalue = strength
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-.73517866 -0.6778734
0.6778734 -0.73517866
Eigenvalues
Eigenvector 1 Eigenvector 2
0.0490834 1.28402771
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-.73517866 -0.6778734
0.6778734 -0.73517866
-.73517866 0.6778734
-0.6778734 -0.73517866
.69 -1.31
.39 .09 1.29
.49 .19 -.81 -.31 -.71
.49 -1.21
.99 .29 1.09
.79 -.31 -.81 -.31 -1.01
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-.828
1.78
-.992
-.27
-1.67
-.912
.099
1.144
.438
1.22
2.5 2.4
0.5 0.7
2.2 2.9
1.9 2.2
3.1 3
2.3 2.7
2 1.6
1 1.1
1.5 1.6
1.1 0.9
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[0,0,0,127, 55, 234, 255, 123, 98… n] n = width * height
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Image1
Image2
Image3
Image4
0 0 0 127
55 234
255
123
98 65
23 15 67 125
76 209
132
64 92 22
76 234
200
98 11o 85 145
97 44 32
209
53 99 198
39 201
38 220
77 92
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Average
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0 0 0 127
55 234
255
123
98 65
23 15 67 125
76 209
132
64 92 22
76 234
200
98 11o
85 145
97 44 32
209
53 99 198
39 201
38 220
77 92
-77 -75.5 -91.5 -10 -1.67 51.75 112.5 -3 20.25 12.25
-54 -60.5 -24.5 -12 19.3 26.75 -10.5 -62 14.25 -30.75
-1 158.5 108.5 -39 53.3 -97.25 2.5 -29 -33.75 -20.75
132 -22.5 7.5 61 -17.67 18.75 -104.5 94 -0.75 39.25
77 75.5 91.5 137 56.67 182.3 142.5 126 77.75 52.75
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Eigenvalues
Eigenvectors
.000064 50.97 84.828 173.8 213.018
-.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
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Animation of reconstruction
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.5 .2 .1
.03 .005
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Demo