1. Label the group photo locate and identify faces and label them

2. Ramona Ciulpan Webmaster Label the group photo locate and identify faces and label them

3. Kornel Toth SVM, Database Label the group photo locate and identify faces and label them

4. Mircea Focşa PPT Presentation Label the group photo locate and identify faces and label them

5. Krisztian Olle Project manager Label the group photo locate and identify faces and label them

6. Project Description Label the group photo- locate and identify faces and label them Input group photo ( for example 10 people) Segment it to isolate people/faces Number the faces Extract the faces Build of library of faces From photos of similar faces try to find that person on the group photo

7. Face Detection Finding faces is complicated?

8. Possible solution Neural Network Template matching Principal Component Analysis Support Vector Machine

9. Possible solution Neural Network Template matching Principal Component Analysis Support Vector Machine

10. Support Vector Machines algorithm Minimize W(Λ)=- Λ T 1 + 1/2 Λ T D Λ Λ Subject to Λ T y = 0 Λ-C 1 0 - Λ 0

11. Face detection (I) Create an images database –266 pictures: 150 faces + 116 non-faces... Preprocessing –Gray scale transformation –Histogram equalization –Adjust resolution to 30x40 pixel Training the SVM based on that 266 vectors, using a polynomial kernel.

12. Face detection (II) Moving over the input image with a 30x40 pixel sub window Histogram equalization of a sub window Classification by SVM Removing intersections

13. Face recognition Training the SVM based on the people faces who want to recognize Classifying the detected faces Labeling the known faces

14. Implementation (I) Input group photo Isolate people / faces Number the faces

15. Implementation (II) Input group photo Isolate people / faces Number the faces

16. Implementation (III) Extract the faces

17. Implementation (IV) Build of library of faces

18. Implementation (V) Label the faces Train the SVM with new set of vectors

19. Results Image nameResolution # of faces # of tests # of found faces Time (sec.) False Classific. csoport.pgm600x3981596001311.456 team2.pgm700x465413020415.0770 team3.pgm600x39849600414.6710 team31.pgm500x33146700410.4990 team4.pgm500x33146700410.5150 team41.pgm400x2654424045.9840 test5.pgm500x3325670049.9371

20. Examples

21. Future Plans Multi-resolution image pyramid Better face databases Better face recognition databases Improve the speed Improve the masking technique

22. Thank You! How many faces ? 1 3 2 456 7 8 9 11 10

23. References Open Source Computer Vision Library Reference Manual http://developer.intel.com/ Guodong Guo, Stan Z. Li, and Kapluk Chan: Face Recognition by Support Vector Machines Proceeding of Fourth IEEE International Conference on Automatic Face and Gesture Recognition, 2000 Grenoble, France. Edgar Osuna, Robert Freund: Training Support Vector Machines: an Application to Face Detection. Proceeding of CVPR97, 1997 Puerto Rico The Face Detection Homepage http://home.t-online.de/home/Robert.Frischholtz/face.htm