PROJECT 4

Tulika Kumar

 

Experiment 1

Data

Face 'class_smiling_cropped\adeakin.tga' recognized as being closest too

0: class_nonsmiling_cropped\adeakin; MSE: 12971.5

1: class_nonsmiling_cropped\ddewey; MSE: 17475.8

2: class_nonsmiling_cropped\tshail; MSE: 25986.7

3: class_nonsmiling_cropped\margaux; MSE: 26480.8

4: class_nonsmiling_cropped\paullarp; MSE: 26717.1

5: class_nonsmiling_cropped\alissah; MSE: 31966.5

6: class_nonsmiling_cropped\tanderl; MSE: 39842.2

7: class_nonsmiling_cropped\crosetti; MSE: 43906.6

8: class_nonsmiling_cropped\djj; MSE: 45935.2

9: class_nonsmiling_cropped\melissa; MSE: 47657

10: class_nonsmiling_cropped\squinn; MSE: 62694.5

11: class_nonsmiling_cropped\mhl; MSE: 66077.5

12: class_nonsmiling_cropped\galen; MSE: 73924

13: class_nonsmiling_cropped\mbixby; MSE: 85813.9

14: class_nonsmiling_cropped\amiratuw; MSE: 91169.2

 

Face 'class_smiling_cropped\alissah.tga' recognized as being closest too:

0: class_nonsmiling_cropped\alissah; MSE: 1545.28

1: class_nonsmiling_cropped\ddewey; MSE: 12063.9

2: class_nonsmiling_cropped\margaux; MSE: 15289.4

3: class_nonsmiling_cropped\paullarp; MSE: 29846.9

4: class_nonsmiling_cropped\adeakin; MSE: 38206.2

5: class_nonsmiling_cropped\amiratuw; MSE: 43612.3

6: class_nonsmiling_cropped\djj; MSE: 54764.4

7: class_nonsmiling_cropped\crosetti; MSE: 65210.2

8: class_nonsmiling_cropped\melissa; MSE: 65691.9

9: class_nonsmiling_cropped\tanderl; MSE: 77631.6

10: class_nonsmiling_cropped\tshail; MSE: 82323.7

11: class_nonsmiling_cropped\tamoore; MSE: 108398

12: class_nonsmiling_cropped\mhl; MSE: 115041

13: class_nonsmiling_cropped\galen; MSE: 127841

14: class_nonsmiling_cropped\esp; MSE: 128921

 

Face 'class_smiling_cropped\amiratuw.tga' recognized as being closest too:

0: class_nonsmiling_cropped\amiratuw; MSE: 5451.23

1: class_nonsmiling_cropped\djj; MSE: 20610

2: class_nonsmiling_cropped\alissah; MSE: 29453.1

3: class_nonsmiling_cropped\ddewey; MSE: 36829.6

4: class_nonsmiling_cropped\margaux; MSE: 38969.9

5: class_nonsmiling_cropped\melissa; MSE: 42387.8

6: class_nonsmiling_cropped\adeakin; MSE: 54551.5

7: class_nonsmiling_cropped\paullarp; MSE: 63749.7

8: class_nonsmiling_cropped\esp; MSE: 67247.2

9: class_nonsmiling_cropped\mbixby; MSE: 73154.7

10: class_nonsmiling_cropped\mhl; MSE: 79840.6

11: class_nonsmiling_cropped\tanderl; MSE: 81446.1

12: class_nonsmiling_cropped\galen; MSE: 85300.7

13: class_nonsmiling_cropped\tshail; MSE: 91688.4

14: class_nonsmiling_cropped\tamoore; MSE: 111765

 

MISS

Face 'class_smiling_cropped\crosetti.tga' recognized as being closest too:

0: class_nonsmiling_cropped\paullarp; MSE: 11474.9

1: class_nonsmiling_cropped\crosetti; MSE: 13384.7

2: class_nonsmiling_cropped\tanderl; MSE: 38688.8

3: class_nonsmiling_cropped\margaux; MSE: 46565.5

4: class_nonsmiling_cropped\ddewey; MSE: 60211.1

5: class_nonsmiling_cropped\alissah; MSE: 60557.4

6: class_nonsmiling_cropped\squinn; MSE: 64998.9

7: class_nonsmiling_cropped\galen; MSE: 74267.5

8: class_nonsmiling_cropped\djj; MSE: 81366.9

9: class_nonsmiling_cropped\esp; MSE: 96283.5

10: class_nonsmiling_cropped\adeakin; MSE: 106503

11: class_nonsmiling_cropped\melissa; MSE: 118889

12: class_nonsmiling_cropped\amiratuw; MSE: 122194

13: class_nonsmiling_cropped\tshail; MSE: 144325

14: class_nonsmiling_cropped\mbixby; MSE: 144515

 

Face 'class_smiling_cropped\ddewey.tga' recognized as being closest too:

0: class_nonsmiling_cropped\ddewey; MSE: 6719.51

1: class_nonsmiling_cropped\margaux; MSE: 9926.03

2: class_nonsmiling_cropped\paullarp; MSE: 10313.4

3: class_nonsmiling_cropped\alissah; MSE: 11112.6

4: class_nonsmiling_cropped\adeakin; MSE: 21519.8

5: class_nonsmiling_cropped\djj; MSE: 26294.8

6: class_nonsmiling_cropped\crosetti; MSE: 32652.3

7: class_nonsmiling_cropped\tanderl; MSE: 34305.4

8: class_nonsmiling_cropped\melissa; MSE: 40315.3

9: class_nonsmiling_cropped\tshail; MSE: 48945.1

10: class_nonsmiling_cropped\amiratuw; MSE: 50120.3

11: class_nonsmiling_cropped\galen; MSE: 64363.8

12: class_nonsmiling_cropped\esp; MSE: 69581.4

13: class_nonsmiling_cropped\squinn; MSE: 69710.3

14: class_nonsmiling_cropped\mhl; MSE: 78876.7

 

Face 'class_smiling_cropped\djj.tga' recognized as being closest too:

0: class_nonsmiling_cropped\djj; MSE: 1505.53

1: class_nonsmiling_cropped\amiratuw; MSE: 20545.8

2: class_nonsmiling_cropped\ddewey; MSE: 27497.5

3: class_nonsmiling_cropped\alissah; MSE: 31505.1

4: class_nonsmiling_cropped\margaux; MSE: 33801.8

5: class_nonsmiling_cropped\esp; MSE: 38910.2

6: class_nonsmiling_cropped\paullarp; MSE: 41929.2

7: class_nonsmiling_cropped\melissa; MSE: 44160.3

8: class_nonsmiling_cropped\adeakin; MSE: 46043.2

9: class_nonsmiling_cropped\tanderl; MSE: 57457.4

10: class_nonsmiling_cropped\tshail; MSE: 68212.8

11: class_nonsmiling_cropped\galen; MSE: 69235.8

12: class_nonsmiling_cropped\mbixby; MSE: 76430.1

13: class_nonsmiling_cropped\crosetti; MSE: 79024.8

14: class_nonsmiling_cropped\mhl; MSE: 82654.1

 

Face 'class_smiling_cropped\esp.tga' recognized as being closest too:

0: class_nonsmiling_cropped\esp; MSE: 14089.7

1: class_nonsmiling_cropped\jwkim; MSE: 31218.2

2: class_nonsmiling_cropped\squinn; MSE: 47588.3

3: class_nonsmiling_cropped\galen; MSE: 55153.4

4: class_nonsmiling_cropped\djj; MSE: 62744.7

5: class_nonsmiling_cropped\tanderl; MSE: 64869.8

6: class_nonsmiling_cropped\mbixby; MSE: 101766

7: class_nonsmiling_cropped\rhennig; MSE: 102708

8: class_nonsmiling_cropped\melissa; MSE: 106763

9: class_nonsmiling_cropped\paullarp; MSE: 108120

10: class_nonsmiling_cropped\amiratuw; MSE: 111242

11: class_nonsmiling_cropped\margaux; MSE: 122465

12: class_nonsmiling_cropped\crosetti; MSE: 144854

13: class_nonsmiling_cropped\mhl; MSE: 148706

14: class_nonsmiling_cropped\alissah; MSE: 152659

 

Face 'class_smiling_cropped\galen.tga' recognized as being closest too:

0: class_nonsmiling_cropped\galen; MSE: 7017.99

1: class_nonsmiling_cropped\mbixby; MSE: 21100.1

2: class_nonsmiling_cropped\squinn; MSE: 34977.8

3: class_nonsmiling_cropped\tanderl; MSE: 52830.5

4: class_nonsmiling_cropped\esp; MSE: 70131

5: class_nonsmiling_cropped\rhennig; MSE: 75794.9

6: class_nonsmiling_cropped\jwkim; MSE: 79978.4

7: class_nonsmiling_cropped\melissa; MSE: 82495

8: class_nonsmiling_cropped\djj; MSE: 87105.1

9: class_nonsmiling_cropped\merlin; MSE: 91923

10: class_nonsmiling_cropped\mhl; MSE: 93998.9

11: class_nonsmiling_cropped\paullarp; MSE: 95291

12: class_nonsmiling_cropped\margaux; MSE: 104535

13: class_nonsmiling_cropped\adeakin; MSE: 106612

14: class_nonsmiling_cropped\ddewey; MSE: 114387

 

Face 'class_smiling_cropped\jaydang.tga' recognized as being closest too:

0: class_nonsmiling_cropped\jaydang; MSE: 26072.5

1: class_nonsmiling_cropped\adeakin; MSE: 31832.5

2: class_nonsmiling_cropped\melissa; MSE: 57447.3

3: class_nonsmiling_cropped\tshail; MSE: 57750.4

4: class_nonsmiling_cropped\ddewey; MSE: 62546.1

5: class_nonsmiling_cropped\mhl; MSE: 66746.2

6: class_nonsmiling_cropped\mbixby; MSE: 96871.2

7: class_nonsmiling_cropped\alissah; MSE: 99376.9

8: class_nonsmiling_cropped\margaux; MSE: 99948

9: class_nonsmiling_cropped\crosetti; MSE: 111441

10: class_nonsmiling_cropped\djj; MSE: 111569

11: class_nonsmiling_cropped\paullarp; MSE: 117774

12: class_nonsmiling_cropped\galen; MSE: 124941

13: class_nonsmiling_cropped\amiratuw; MSE: 132598

14: class_nonsmiling_cropped\esp; MSE: 146181

 

Face 'class_smiling_cropped\jwkim.tga' recognized as being closest too:

0: class_nonsmiling_cropped\jwkim; MSE: 5318.32

1: class_nonsmiling_cropped\esp; MSE: 36372

2: class_nonsmiling_cropped\squinn; MSE: 51489.8

3: class_nonsmiling_cropped\mbixby; MSE: 57382.3

4: class_nonsmiling_cropped\galen; MSE: 59903.8

5: class_nonsmiling_cropped\rhennig; MSE: 67378

6: class_nonsmiling_cropped\djj; MSE: 78457

7: class_nonsmiling_cropped\tanderl; MSE: 79888.8

8: class_nonsmiling_cropped\mhl; MSE: 80216.3

9: class_nonsmiling_cropped\melissa; MSE: 84405.8

10: class_nonsmiling_cropped\amiratuw; MSE: 126496

11: class_nonsmiling_cropped\merlin; MSE: 138451

12: class_nonsmiling_cropped\margaux; MSE: 144899

13: class_nonsmiling_cropped\tamoore; MSE: 147098

14: class_nonsmiling_cropped\tshail; MSE: 149874

 

Face 'class_smiling_cropped\margaux.tga' recognized as being closest too:

0: class_nonsmiling_cropped\margaux; MSE: 3719.92

1: class_nonsmiling_cropped\paullarp; MSE: 12796.7

2: class_nonsmiling_cropped\alissah; MSE: 14019

3: class_nonsmiling_cropped\ddewey; MSE: 29398.8

4: class_nonsmiling_cropped\tanderl; MSE: 30012.5

5: class_nonsmiling_cropped\djj; MSE: 42968.6

6: class_nonsmiling_cropped\amiratuw; MSE: 45975.4

7: class_nonsmiling_cropped\crosetti; MSE: 47608.7

8: class_nonsmiling_cropped\melissa; MSE: 47660.2

9: class_nonsmiling_cropped\adeakin; MSE: 58976.9

10: class_nonsmiling_cropped\galen; MSE: 71399

11: class_nonsmiling_cropped\squinn; MSE: 78519.9

12: class_nonsmiling_cropped\esp; MSE: 80193.4

13: class_nonsmiling_cropped\tshail; MSE: 91887

14: class_nonsmiling_cropped\mhl; MSE: 101041

 

Face 'class_smiling_cropped\mbixby.tga' recognized as being closest too:

0: class_nonsmiling_cropped\mbixby; MSE: 2258.52

1: class_nonsmiling_cropped\galen; MSE: 37787.5

2: class_nonsmiling_cropped\rhennig; MSE: 45390

3: class_nonsmiling_cropped\esp; MSE: 74745

4: class_nonsmiling_cropped\melissa; MSE: 75825.9

5: class_nonsmiling_cropped\squinn; MSE: 76587.4

6: class_nonsmiling_cropped\mhl; MSE: 79003.6

7: class_nonsmiling_cropped\djj; MSE: 79182.7

8: class_nonsmiling_cropped\adeakin; MSE: 81109.6

9: class_nonsmiling_cropped\tanderl; MSE: 87006.2

10: class_nonsmiling_cropped\ddewey; MSE: 96382.8

11: class_nonsmiling_cropped\jwkim; MSE: 96566.7

12: class_nonsmiling_cropped\amiratuw; MSE: 104545

13: class_nonsmiling_cropped\paullarp; MSE: 111185

14: class_nonsmiling_cropped\margaux; MSE: 115328

 

Face 'class_smiling_cropped\melissa.tga' recognized as being closest too:

0: class_nonsmiling_cropped\melissa; MSE: 15549.8

1: class_nonsmiling_cropped\margaux; MSE: 19682.6

2: class_nonsmiling_cropped\adeakin; MSE: 20250.4

3: class_nonsmiling_cropped\ddewey; MSE: 28311

4: class_nonsmiling_cropped\tshail; MSE: 29713.4

5: class_nonsmiling_cropped\mhl; MSE: 33875.5

6: class_nonsmiling_cropped\tanderl; MSE: 34550.6

7: class_nonsmiling_cropped\djj; MSE: 35032.2

8: class_nonsmiling_cropped\paullarp; MSE: 35709.1

9: class_nonsmiling_cropped\alissah; MSE: 36289.2

10: class_nonsmiling_cropped\squinn; MSE: 48848.8

11: class_nonsmiling_cropped\galen; MSE: 53573.1

12: class_nonsmiling_cropped\crosetti; MSE: 60178.3

13: class_nonsmiling_cropped\esp; MSE: 62472.8

14: class_nonsmiling_cropped\amiratuw; MSE: 66584.4

 

Face 'class_smiling_cropped\merlin.tga' recognized as being closest too:

0: class_nonsmiling_cropped\merlin; MSE: 54097.6

1: class_nonsmiling_cropped\seitz; MSE: 85327.6

2: class_nonsmiling_cropped\squinn; MSE: 220206

3: class_nonsmiling_cropped\jwkim; MSE: 233301

4: class_nonsmiling_cropped\rhennig; MSE: 242120

5: class_nonsmiling_cropped\galen; MSE: 243982

6: class_nonsmiling_cropped\mbixby; MSE: 296636

7: class_nonsmiling_cropped\tanderl; MSE: 314179

8: class_nonsmiling_cropped\esp; MSE: 316868

9: class_nonsmiling_cropped\mhl; MSE: 369628

10: class_nonsmiling_cropped\djj; MSE: 370419

11: class_nonsmiling_cropped\tshail; MSE: 373193

12: class_nonsmiling_cropped\melissa; MSE: 425440

13: class_nonsmiling_cropped\adeakin; MSE: 452167

14: class_nonsmiling_cropped\paullarp; MSE: 463344

 

MISS

Face 'class_smiling_cropped\mhl.tga' recognized as being closest too:

0: class_nonsmiling_cropped\melissa; MSE: 18586

1: class_nonsmiling_cropped\margaux; MSE: 19253.1

2: class_nonsmiling_cropped\alissah; MSE: 23861

3: class_nonsmiling_cropped\amiratuw; MSE: 31874.5

4: class_nonsmiling_cropped\ddewey; MSE: 39507.8

5: class_nonsmiling_cropped\adeakin; MSE: 43503.8

6: class_nonsmiling_cropped\mhl; MSE: 45869.8

7: class_nonsmiling_cropped\djj; MSE: 47391.2

8: class_nonsmiling_cropped\paullarp; MSE: 53074.3

9: class_nonsmiling_cropped\tanderl; MSE: 56036.7

10: class_nonsmiling_cropped\tshail; MSE: 75530.9

11: class_nonsmiling_cropped\mbixby; MSE: 82231.2

12: class_nonsmiling_cropped\galen; MSE: 82966.3

13: class_nonsmiling_cropped\esp; MSE: 83415.9

14: class_nonsmiling_cropped\tamoore; MSE: 93043.6

 

MISS

Face 'class_smiling_cropped\paullarp.tga' recognized as being closest too:

0: class_nonsmiling_cropped\alissah; MSE: 8043.42

1: class_nonsmiling_cropped\ddewey; MSE: 18170.5

2: class_nonsmiling_cropped\margaux; MSE: 30119.1

3: class_nonsmiling_cropped\paullarp; MSE: 32758

4: class_nonsmiling_cropped\adeakin; MSE: 55002.2

5: class_nonsmiling_cropped\crosetti; MSE: 58496.4

6: class_nonsmiling_cropped\amiratuw; MSE: 63450.6

7: class_nonsmiling_cropped\djj; MSE: 79203.4

8: class_nonsmiling_cropped\melissa; MSE: 96317

9: class_nonsmiling_cropped\tanderl; MSE: 99127.8

10: class_nonsmiling_cropped\tshail; MSE: 113632

11: class_nonsmiling_cropped\tamoore; MSE: 126909

12: class_nonsmiling_cropped\galen; MSE: 154036

13: class_nonsmiling_cropped\esp; MSE: 155167

14: class_nonsmiling_cropped\mbixby; MSE: 158154

 

Face 'class_smiling_cropped\rhennig.tga' recognized as being closest too:

0: class_nonsmiling_cropped\rhennig; MSE: 15227.6

1: class_nonsmiling_cropped\mbixby; MSE: 37176.5

2: class_nonsmiling_cropped\galen; MSE: 75458.8

3: class_nonsmiling_cropped\merlin; MSE: 86999.2

4: class_nonsmiling_cropped\jwkim; MSE: 96211.5

5: class_nonsmiling_cropped\esp; MSE: 97532.4

6: class_nonsmiling_cropped\squinn; MSE: 99232.3

7: class_nonsmiling_cropped\mhl; MSE: 124113

8: class_nonsmiling_cropped\melissa; MSE: 140080

9: class_nonsmiling_cropped\djj; MSE: 141374

10: class_nonsmiling_cropped\tanderl; MSE: 154893

11: class_nonsmiling_cropped\adeakin; MSE: 161880

12: class_nonsmiling_cropped\tshail; MSE: 176267

13: class_nonsmiling_cropped\ddewey; MSE: 196962

14: class_nonsmiling_cropped\amiratuw; MSE: 203321

 

Face 'class_smiling_cropped\seitz.tga' recognized as being closest too:

0: class_nonsmiling_cropped\seitz; MSE: 40058.3

1: class_nonsmiling_cropped\merlin; MSE: 50515.8

2: class_nonsmiling_cropped\squinn; MSE: 76255.6

3: class_nonsmiling_cropped\galen; MSE: 100420

4: class_nonsmiling_cropped\tanderl; MSE: 122101

5: class_nonsmiling_cropped\rhennig; MSE: 151157

6: class_nonsmiling_cropped\esp; MSE: 154275

7: class_nonsmiling_cropped\jwkim; MSE: 160881

8: class_nonsmiling_cropped\djj; MSE: 167037

9: class_nonsmiling_cropped\mbixby; MSE: 170901

10: class_nonsmiling_cropped\tshail; MSE: 173804

11: class_nonsmiling_cropped\paullarp; MSE: 183272

12: class_nonsmiling_cropped\crosetti; MSE: 187661

13: class_nonsmiling_cropped\adeakin; MSE: 212541

14: class_nonsmiling_cropped\margaux; MSE: 222984

 

Face 'class_smiling_cropped\squinn.tga' recognized as being closest too:

0: class_nonsmiling_cropped\squinn; MSE: 52543.6

1: class_nonsmiling_cropped\seitz; MSE: 74801.5

2: class_nonsmiling_cropped\merlin; MSE: 87844.8

3: class_nonsmiling_cropped\jwkim; MSE: 110926

4: class_nonsmiling_cropped\galen; MSE: 111005

5: class_nonsmiling_cropped\tanderl; MSE: 120372

6: class_nonsmiling_cropped\rhennig; MSE: 145225

7: class_nonsmiling_cropped\esp; MSE: 166183

8: class_nonsmiling_cropped\mbixby; MSE: 166589

9: class_nonsmiling_cropped\mhl; MSE: 216921

10: class_nonsmiling_cropped\paullarp; MSE: 220648

11: class_nonsmiling_cropped\djj; MSE: 222511

12: class_nonsmiling_cropped\tshail; MSE: 226352

13: class_nonsmiling_cropped\melissa; MSE: 234237

14: class_nonsmiling_cropped\crosetti; MSE: 240891

 

Face 'class_smiling_cropped\tamoore.tga' recognized as being closest too:

0: class_nonsmiling_cropped\tamoore; MSE: 9094.35

1: class_nonsmiling_cropped\tanderl; MSE: 109749

2: class_nonsmiling_cropped\mhl; MSE: 110799

3: class_nonsmiling_cropped\adeakin; MSE: 114652

4: class_nonsmiling_cropped\djj; MSE: 117339

5: class_nonsmiling_cropped\alissah; MSE: 120425

6: class_nonsmiling_cropped\tshail; MSE: 121884

7: class_nonsmiling_cropped\jwkim; MSE: 123171

8: class_nonsmiling_cropped\melissa; MSE: 130021

9: class_nonsmiling_cropped\margaux; MSE: 130358

10: class_nonsmiling_cropped\ddewey; MSE: 134084

11: class_nonsmiling_cropped\squinn; MSE: 146091

12: class_nonsmiling_cropped\paullarp; MSE: 149230

13: class_nonsmiling_cropped\amiratuw; MSE: 152695

14: class_nonsmiling_cropped\mbixby; MSE: 153428

 

Face 'class_smiling_cropped\tanderl.tga' recognized as being closest too:

0: class_nonsmiling_cropped\tanderl; MSE: 8774.5

1: class_nonsmiling_cropped\paullarp; MSE: 21155

2: class_nonsmiling_cropped\squinn; MSE: 31939.3

3: class_nonsmiling_cropped\margaux; MSE: 36038.9

4: class_nonsmiling_cropped\djj; MSE: 40251.3

5: class_nonsmiling_cropped\galen; MSE: 40468.4

6: class_nonsmiling_cropped\ddewey; MSE: 43697.9

7: class_nonsmiling_cropped\alissah; MSE: 46435.6

8: class_nonsmiling_cropped\crosetti; MSE: 55920

9: class_nonsmiling_cropped\adeakin; MSE: 56835.2

10: class_nonsmiling_cropped\esp; MSE: 67441.6

11: class_nonsmiling_cropped\mbixby; MSE: 67831.2

12: class_nonsmiling_cropped\melissa; MSE: 73662

13: class_nonsmiling_cropped\tshail; MSE: 74045.6

14: class_nonsmiling_cropped\amiratuw; MSE: 89548.4

 

Face 'class_smiling_cropped\tshail.tga' recognized as being closest too:

0: class_nonsmiling_cropped\tshail; MSE: 2435.51

1: class_nonsmiling_cropped\adeakin; MSE: 10348.2

2: class_nonsmiling_cropped\ddewey; MSE: 36649.9

3: class_nonsmiling_cropped\mhl; MSE: 40087.8

4: class_nonsmiling_cropped\melissa; MSE: 42589.7

5: class_nonsmiling_cropped\margaux; MSE: 45213.8

6: class_nonsmiling_cropped\alissah; MSE: 53722.2

7: class_nonsmiling_cropped\djj; MSE: 60015.6

8: class_nonsmiling_cropped\paullarp; MSE: 76386.2

9: class_nonsmiling_cropped\tanderl; MSE: 84556.2

10: class_nonsmiling_cropped\amiratuw; MSE: 100796

11: class_nonsmiling_cropped\crosetti; MSE: 104301

12: class_nonsmiling_cropped\jaydang; MSE: 106143

13: class_nonsmiling_cropped\tamoore; MSE: 109623

14: class_nonsmiling_cropped\squinn; MSE: 114716

 

Answers To Questions  

1)Out of 22 people, 19 identified correctly, 3 incorrectly.

2)In the cases where identification was incorrect, the person was listed on average as (4+7+2)/3 approximately 4th.

3)When a female face is recognized, it is not the case that the next few best matches are females.  And when a male face is recognized, it is not the case either that the next few best matches are male.  In all the cases where a female was recognized, there is no case where the next 4 best matches are female.  Only 1 female had the next 3 best matches be females.  For the rest of the females that were recognized, the second and third best matches are about evenly spread out between males and females.  In all cases where a male was recognized, there is no case where the next 4 best matches are all males.  Only 2 males had the next 3 best matches be male.  For the rest of the males that were recognized, the second and third best matches are about evenly spaced out between males and females. 

4) There are tradeoffs with using a large number of users to compute your face space.  The larger the number of users you use to compute your face space, the better your representation of human faces.  As we have witnessed from carrying out this project, the method of using eigenfaces to compute the face space takes minutes for less than 20 users.  If the application for which you are using a face recognition system requires great accuracy, then you should use a larger number of training samples to compute the face space.  If your application doesn’t require great accuracy, then you don’t need to use such a large number of training samples.  If you have a big powerful computer that can do computations really fast, then you can use more training samples.  So in short, the answer to this question depends on the application and the time you are willing to spend waiting for your face space to be computed.   You don't need to train on thousands of faces to get good results though.

5)The only case I can see in which it would be good to train your face space on samples other than pictures used for actual recognition is if you’re trying to determine how well your space face can generalize to new faces.  Say you’ve come up with a new algorithm for computing faces spaces.  If you use a set of pictures to compute this face space, your face space may be suited for recognizing only those faces it has been trained on.  This isn’t a very useful algorithm then.  By using samples not used in training, you can see how well the face space generalizes to new input. 

Pictures Of Results

The average face - I used 25x25 pixel images (Sorry they're so small to see!).

    

The seven eigenfaces

 

Experiment 2

Data

Training Face Space on 5 faces:

Correct recognitions:  2/5   Incorrect 3/5.

Correct Recognition Rate: 40%

Training Face Space on 10 faces:

Correct recognitions:  3/10   Incorrect 7/10.

Correct Recognition Rate: 30%

Training Face Space on 12 faces:

Correct recognitions:  5/12   Incorrect: 7/12

Correct Recognition Rate: 42%

Training Face Space on 15 faces:

Correct recognitions:  6/15   Incorrect: 9/15

Correct Recognition Rate: 40%

Training Face Space on 20 faces:

Correct recognitions:  8/20   Incorrect: 12/20

Correct Recognition Rate: 40%

Answers To Questions

1)  (Data for experiment shown above)

2) The incorrect recognitions were usually quite off.  For example, when I computed the faces space 

with 20 users and tried to recognize "adeakin", I got that the best result was "melissa" and that the 

5th best result was "adeakin."   

 

  adeakin                 melissa

          

 

And when I computed the face space with 15 users and tried to recognize "merlin", I got that the best

result was "alissah" and that the 9th best result was "merlin."

 

   merlin                     alissah

             

 

3) Here are some reasons why the program performed more poorly in recognizing people:

- Pictures of people taken in our class are (in general) very different from our undergraduate pictures.

In the undergraduate pictures people have very different facial expressions, very different angles in

which theyare facing the camera, etc.  In the first experiment, the camera angles were kept the same

(the person is staring straight ahead) and the facial expressions didn't change a whole lot (a lot of smiles

are like the nonsmiles :).  This is partly why we got better results in the first experiment.  The matches were

more clear in the first experiment.  Here they were not because of the great variability between people's 

pictures in the undergraduate and class sets. 

-We used less eigenfaces in our face space (or we used fewer faces from which to compute our face space). 

To some extent the fewer faces you use to construct your face space, the more difficult it will be to correctly

interpolate other faces. 

-We used a larger database to compute the eigenfaces from.  We probably constructed face space from 

people NOT is our class.  So when we computed the coefficients for the people in our class, they weren't

as accurate as in experiment 1.  There was probably some error in interpolating our class pictures in face

space composed from people not in our class.  

4)  Actually, changing the number of eigenfaces didn't change the percentage of correct recognitions much.

All of the different number eigenfaces gave about 40% correct recognition except for when I used 10 (in 

which case I got 30% correct recognition).  The factors I mentioned in question 3 are mostly why I didn't

see an improvement in recognition accuracy as I increased the number of eigenfaces in my face space.  I got

the best recognition when I used 12 eigenfaces (42% accuracy).

5)  One reason I can think of using as few eigenfaces as possible (and still get good results) is that

it is pretty time costly to compute the eigenfaces (at least with the method that we used in this project).

 

Pictures Of Results

The average face for 5 training samples

Eigenfaces for face space constructed from 5 training samples

               

The average face for 10 training samples

Eigenfaces for face space constructed from 10 training samples

                                   

The average face for 12 training samples

Eigenfaces for face space constructed from 12 training samples

                                           

The average face for 15 training samples

Eigenfaces for face space constructed from 15 training samples

                                                      

The average face for 20 training samples

Eigenfaces for face space constructed from 20 training samples

                                                                           

 

Experiment 3

Answers To Questions  

1) For min_scale I used 0.2.  For max_scale I used 0.3.  For step I used 0.05.

2)  None of my cropped results get the students EXACTLY in the center.  Everyone is

cut off on one side or the other a bit.  But in each of the 10 cropped images I get almost all

off the person's face.  See the picture results below to see what I mean.  

3) If you use a min_scale that is too small, the size of your rescaled image can be

smaller than the box you use to go through and look for faces.  Also, if you make your

original image really small, you lose some of its detail.  A face may look nothing like a 

face if the image is scaled too small. 

Pictures Of Results

So here is the result of me cropping myself.  As you can see the result is ok.

 I got most of my face, but the right side is cut of somewhat.

 

       Me - Uncropped (AHHH!)        

     

Me - Cropped (AHHHHHHHHHHHHH!)

 

This was one of the best results I got.  Just about all of Linn's face is showing...

                Linn Uncropped

                Linn Cropped

 

The cropped picture of albert below didn't turn out that well - he's missing much of

his right face!

Albert Uncropped

Albert Cropped

 

The one of Corey below is also one of my best results.

Corey Uncropped

Corey Cropped

 

I guess my cropped results weren't that good!

 

Experiment 4

Answers To Questions  

1) For my birthday picture I used min_scale = 0.9, max_scale = 0.95, step = 0.05.

For denzel's picture, I used min_scale = 0.4, max_scale = 0.5, step = 0.05.

2) As you can see the major problem I had in detecting faces in both images is that my program

detected low-textured regions as "faces."  Low-textured regions lie in the hyperplane of faces - 

there are non-face things in this hyperplane.  They're in the hyperplane (or close to it), but they

 are far from the facial mean (as compared to actual faces).  So one thing I should have done

 perhaps is check the MSE of each subimage (with the average face) to see if I have something that's

 even close to what an average face looks like.  If it's not even close to what an average face looks

 like, toss it out.  

Another way perhaps to get rid of low-textured region detection would be to look at the variance of the pixels

in the subimage.  If the variance is really smalll, it's probably a sweatshirt or something, not a face (it'll

be a part of the image in which all the pixels are the same color.  Though most face pixels are sorta close

to one another, there's definitely more variation in the pixels of a face than say the night sky so well

found in my birthday picture.  So this way I shouldn't detect the squares I ended up detecting in both

images).

 

Pictures Of Results

 

My last birthday - original

 Here's the result of trying to find faces in my birthday picture:

 

DENZEL! - original

Here's the result of trying to find faces in denzel's picture: