Eigenfaces for Recognition By: Matthew Turk and Alex Pentland 1991 IEEE
Eigenfaces for Recognition - CS Course...
Transcript of Eigenfaces for Recognition - CS Course...
![Page 1: Eigenfaces for Recognition - CS Course Webpagescourses.cs.tamu.edu/rgutier/cpsc689_s07/turkPentland1991eigenfaces... · 1 Eigenfaces for Recognition (Turk, Pentland; 1991) Pedro Davalos](https://reader031.fdocuments.net/reader031/viewer/2022022110/5c1df1fd09d3f2ef218c4241/html5/thumbnails/1.jpg)
1
Eigenfaces for Recognition(Turk, Pentland; 1991)
Pedro DavalosCPSC 689-604Apr 10, 2007
![Page 2: Eigenfaces for Recognition - CS Course Webpagescourses.cs.tamu.edu/rgutier/cpsc689_s07/turkPentland1991eigenfaces... · 1 Eigenfaces for Recognition (Turk, Pentland; 1991) Pedro Davalos](https://reader031.fdocuments.net/reader031/viewer/2022022110/5c1df1fd09d3f2ef218c4241/html5/thumbnails/2.jpg)
2
Outline
• Background• PCA (Eigenfaces)• Issues• Face Detection• Experiments / Tests• Comments / Conclusion
![Page 3: Eigenfaces for Recognition - CS Course Webpagescourses.cs.tamu.edu/rgutier/cpsc689_s07/turkPentland1991eigenfaces... · 1 Eigenfaces for Recognition (Turk, Pentland; 1991) Pedro Davalos](https://reader031.fdocuments.net/reader031/viewer/2022022110/5c1df1fd09d3f2ef218c4241/html5/thumbnails/3.jpg)
3
Face Recognition Background• “Traditional” approaches use bottom-up Feature analysis
and geometric measurements
• Additional methods include – Deformable templates– Multiresolution templates– Connectionists approaches
Piecemeal Approach
![Page 4: Eigenfaces for Recognition - CS Course Webpagescourses.cs.tamu.edu/rgutier/cpsc689_s07/turkPentland1991eigenfaces... · 1 Eigenfaces for Recognition (Turk, Pentland; 1991) Pedro Davalos](https://reader031.fdocuments.net/reader031/viewer/2022022110/5c1df1fd09d3f2ef218c4241/html5/thumbnails/4.jpg)
4
Eigenface Approach• GOAL:
– Develop a fast, simple, and accurate face recognition computational model
• Assumptions – 2-D images, – Centered frontal portrait
• Method– Use Information Theory to analyze data– Encode images through Principal Components Analysis (PCA)
Holistic Approach
![Page 5: Eigenfaces for Recognition - CS Course Webpagescourses.cs.tamu.edu/rgutier/cpsc689_s07/turkPentland1991eigenfaces... · 1 Eigenfaces for Recognition (Turk, Pentland; 1991) Pedro Davalos](https://reader031.fdocuments.net/reader031/viewer/2022022110/5c1df1fd09d3f2ef218c4241/html5/thumbnails/5.jpg)
5
Eigenface training (1 of 2)• M=16 images (255x255 pixels)
– Each image vector Γ is 65536x1– Input images: S = [Γ1, Γ2, … , Γ16] (16x65536)
• Average Face is Ψ (65536x1)
• Each Image differs from mean Φ=Γ -Ψ
• Input faces A = [Φ1, Φ2, Φ3, … ,Φ16] (16x65536)
Valentine’s Norm-based coding in high dimensional face space
![Page 6: Eigenfaces for Recognition - CS Course Webpagescourses.cs.tamu.edu/rgutier/cpsc689_s07/turkPentland1991eigenfaces... · 1 Eigenfaces for Recognition (Turk, Pentland; 1991) Pedro Davalos](https://reader031.fdocuments.net/reader031/viewer/2022022110/5c1df1fd09d3f2ef218c4241/html5/thumbnails/6.jpg)
6
Eigenface training (2 of 2)• Covariance Matrix to find Eigenvalues L = ATA (16x16)
• Calculate eigenvectors v=eig(L) (16x16)
• Obtain EigenFaces u=v*A (16x65536)
• Determine significant Eigenvalues/Eigenvectors to utilize M’ eigenfaceswith most information
• Encode input faces into low dimensional space through “weights”
Each Image is only represented by a vector of size M’ (7) instead of N2 (65536)
![Page 7: Eigenfaces for Recognition - CS Course Webpagescourses.cs.tamu.edu/rgutier/cpsc689_s07/turkPentland1991eigenfaces... · 1 Eigenfaces for Recognition (Turk, Pentland; 1991) Pedro Davalos](https://reader031.fdocuments.net/reader031/viewer/2022022110/5c1df1fd09d3f2ef218c4241/html5/thumbnails/7.jpg)
7
Recognition using Eigenfaces• Calculate ‘weights’ of unknown Input face (Γ)
• Compute Euclidean Distance from input face ‘weights’ to training images. Closest match wins!
![Page 8: Eigenfaces for Recognition - CS Course Webpagescourses.cs.tamu.edu/rgutier/cpsc689_s07/turkPentland1991eigenfaces... · 1 Eigenfaces for Recognition (Turk, Pentland; 1991) Pedro Davalos](https://reader031.fdocuments.net/reader031/viewer/2022022110/5c1df1fd09d3f2ef218c4241/html5/thumbnails/8.jpg)
8
Eigenfaces Overview
subtracti=1…M’“Eigenfaces”
dot
Database of M input images, each represented by their M’weights Ω
ε Distance from input Ω to database
Select min distance
Face space distance
Face class distance
![Page 9: Eigenfaces for Recognition - CS Course Webpagescourses.cs.tamu.edu/rgutier/cpsc689_s07/turkPentland1991eigenfaces... · 1 Eigenfaces for Recognition (Turk, Pentland; 1991) Pedro Davalos](https://reader031.fdocuments.net/reader031/viewer/2022022110/5c1df1fd09d3f2ef218c4241/html5/thumbnails/9.jpg)
9
Adaptive Learning
• Eigenfaces Bonus Feature– If an unknown input face is both
• Close to face-space and• Not Close to any face in the database
– Then• It is a potentially new face• The new face can be added to the database
Unsupervised Operation
![Page 10: Eigenfaces for Recognition - CS Course Webpagescourses.cs.tamu.edu/rgutier/cpsc689_s07/turkPentland1991eigenfaces... · 1 Eigenfaces for Recognition (Turk, Pentland; 1991) Pedro Davalos](https://reader031.fdocuments.net/reader031/viewer/2022022110/5c1df1fd09d3f2ef218c4241/html5/thumbnails/10.jpg)
10
Face Detection (not recognition)• 1 – Motion Analysis (optic flow)
– nothing to do with PCA– Fails with various moving
objects– Fails without people moving
• 2 – Face Space– Eigenface template matching
Ideal
![Page 11: Eigenfaces for Recognition - CS Course Webpagescourses.cs.tamu.edu/rgutier/cpsc689_s07/turkPentland1991eigenfaces... · 1 Eigenfaces for Recognition (Turk, Pentland; 1991) Pedro Davalos](https://reader031.fdocuments.net/reader031/viewer/2022022110/5c1df1fd09d3f2ef218c4241/html5/thumbnails/11.jpg)
11
Issues• Background• Scale/Size• Orientation/rotation• 3d Viewpoint• Expressions• Lighting• Makeup
![Page 12: Eigenfaces for Recognition - CS Course Webpagescourses.cs.tamu.edu/rgutier/cpsc689_s07/turkPentland1991eigenfaces... · 1 Eigenfaces for Recognition (Turk, Pentland; 1991) Pedro Davalos](https://reader031.fdocuments.net/reader031/viewer/2022022110/5c1df1fd09d3f2ef218c4241/html5/thumbnails/12.jpg)
12
Results2: unknown
Light: 19%
Orientation: 39%
Scale: 60%
Experiments: 1- robustness
• Testing three independent variables identified as potential issues: lighting, scale, orientation
orientation
light
scale
Results1: correct
Light: 96%
Orientation: 85%
Scale: 64%
![Page 13: Eigenfaces for Recognition - CS Course Webpagescourses.cs.tamu.edu/rgutier/cpsc689_s07/turkPentland1991eigenfaces... · 1 Eigenfaces for Recognition (Turk, Pentland; 1991) Pedro Davalos](https://reader031.fdocuments.net/reader031/viewer/2022022110/5c1df1fd09d3f2ef218c4241/html5/thumbnails/13.jpg)
13
Eigenface Enhancement Extensions• Shape-free faces potentially addresses issues
• Eliminate Background through gaussian
• Rotate tilted face by pre-process
• Address scale variance through multiscale training or size estimation through pre-processing
Craw, 1995; Craw & Cameron, 1991; Burton, Bruce, and Hancock, 1999
φ
![Page 14: Eigenfaces for Recognition - CS Course Webpagescourses.cs.tamu.edu/rgutier/cpsc689_s07/turkPentland1991eigenfaces... · 1 Eigenfaces for Recognition (Turk, Pentland; 1991) Pedro Davalos](https://reader031.fdocuments.net/reader031/viewer/2022022110/5c1df1fd09d3f2ef218c4241/html5/thumbnails/14.jpg)
14
>data_
![Page 16: Eigenfaces for Recognition - CS Course Webpagescourses.cs.tamu.edu/rgutier/cpsc689_s07/turkPentland1991eigenfaces... · 1 Eigenfaces for Recognition (Turk, Pentland; 1991) Pedro Davalos](https://reader031.fdocuments.net/reader031/viewer/2022022110/5c1df1fd09d3f2ef218c4241/html5/thumbnails/16.jpg)
16
![Page 17: Eigenfaces for Recognition - CS Course Webpagescourses.cs.tamu.edu/rgutier/cpsc689_s07/turkPentland1991eigenfaces... · 1 Eigenfaces for Recognition (Turk, Pentland; 1991) Pedro Davalos](https://reader031.fdocuments.net/reader031/viewer/2022022110/5c1df1fd09d3f2ef218c4241/html5/thumbnails/17.jpg)
17
Demo (1/4)
http://www.pages.drexel.edu/~sis26/Eigenface%20Tutorial.htm
![Page 18: Eigenfaces for Recognition - CS Course Webpagescourses.cs.tamu.edu/rgutier/cpsc689_s07/turkPentland1991eigenfaces... · 1 Eigenfaces for Recognition (Turk, Pentland; 1991) Pedro Davalos](https://reader031.fdocuments.net/reader031/viewer/2022022110/5c1df1fd09d3f2ef218c4241/html5/thumbnails/18.jpg)
18
Demo (2/4)
![Page 19: Eigenfaces for Recognition - CS Course Webpagescourses.cs.tamu.edu/rgutier/cpsc689_s07/turkPentland1991eigenfaces... · 1 Eigenfaces for Recognition (Turk, Pentland; 1991) Pedro Davalos](https://reader031.fdocuments.net/reader031/viewer/2022022110/5c1df1fd09d3f2ef218c4241/html5/thumbnails/19.jpg)
19
Demo (3/4)
x104
![Page 20: Eigenfaces for Recognition - CS Course Webpagescourses.cs.tamu.edu/rgutier/cpsc689_s07/turkPentland1991eigenfaces... · 1 Eigenfaces for Recognition (Turk, Pentland; 1991) Pedro Davalos](https://reader031.fdocuments.net/reader031/viewer/2022022110/5c1df1fd09d3f2ef218c4241/html5/thumbnails/20.jpg)
20
Demo (4/4)
![Page 21: Eigenfaces for Recognition - CS Course Webpagescourses.cs.tamu.edu/rgutier/cpsc689_s07/turkPentland1991eigenfaces... · 1 Eigenfaces for Recognition (Turk, Pentland; 1991) Pedro Davalos](https://reader031.fdocuments.net/reader031/viewer/2022022110/5c1df1fd09d3f2ef218c4241/html5/thumbnails/21.jpg)
21
Eigenfaces Applications
• Recognition/Authentication• Face Detection/Location• Compression/Storage• Reconstruct Occlusions• Actor segmentation for video• Facial expression detector
![Page 22: Eigenfaces for Recognition - CS Course Webpagescourses.cs.tamu.edu/rgutier/cpsc689_s07/turkPentland1991eigenfaces... · 1 Eigenfaces for Recognition (Turk, Pentland; 1991) Pedro Davalos](https://reader031.fdocuments.net/reader031/viewer/2022022110/5c1df1fd09d3f2ef218c4241/html5/thumbnails/22.jpg)
22
Conclusions
• Implementation of a computational model for recognition • Dimensionality Reduction• Holistic approach• PCA can be used to recognize other objects• Thresholds have a significant effect