1. Face Recognition System By Arthur

2. Introduction  A facial recognition system is a computer application for automatically identifying or verifying a person from a digital image or a video frame from a video source. --Wikipedia  Face perception  Machine Learning Example  http://how-old.net/ (Microsoft) http://how-old.net/

3. Basic Face Recognition System

4. Step 1: Face detection  Identify and locate human faces  Normalization Face detection methods:  Knowledge-based methods  Feature invariant approaches  Template matching methods  Appearance-based methods

5. Step 2: Feature extraction  Holistic Feature Extraction  Eigenface  principal component analysis (PCA)  Local Feature Extraction  Gabor Wavelet Transform

6. Eigenface and PCA

7. Example

8. Step 3: Face recognition/verification  Verification  Recognition  Match  Database:The Yale Face Database

9. Applications  Entertainment: Smart camera/ Virtual Reality  Smart Cards: Passports  Security : Personal Device Logon /Real time screening  Law Enforcement: Anti-crime

10. Advantages  Non-intrusive biometric identification technique  Convenient and economic  Real time screening

11. Disadvantages  Strict requirement of light and pose  Face may change with time  Privacy issue

12. Conclusion  A popular research area in machine leaning with a broad application foreground.

13. Reference  M. Turk, A. Pentland, Eigenfaces for Recognition, Journal of Cognitive Neurosicence, Vol. 3, No. 1, 1991, pp. 71-86  A. Pentland, B. Moghaddam, T. Starner, View-Based and Modular Eigenspaces for Face Recognition, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 21-23 June 1994, Seattle, Washington, USA, pp. 84- 91  H. Moon, P.J. Phillips, Computational and Performance aspects of PCA-based Face Recognition Algorithms, Perception, Vol. 30, 2001, pp. 303-321

14. Thank you!