1. Keep Smiling! GRIM GRINS

2. The Project’s member György Hingyi – programmer & manager1 Péter Szabó – programmer & manager2 Sinan Oz – scientist Krisztina Maróti – do „paper” work

3. The problem Smiling faces. Input : a set of photos of the same person with different face expressions and the information that some of them are smiling faces Task : to write a program (e.g., neural network) recognizing the smiling faces of the same person Output : smiling or not, and the statistics of the implemented method. Difficulty : hard

4. Method Selection K-nearest neighbors Neural networks Ensembles of neural network classifiers Set of experts Support Vector Machine Other methods – Other New brainchild Etc…

5. Other’s works Real-Time Emotion Recognition using Biologically Inspired Models Keith Anderson, Peter W. McOwan – Using SVM Recognizing Emotion From Facial Expressions: Psychological and Neurological Mechanisms Ralph Adolphs University of Iowa College of Medicine – Using Others Recognizing Emotion in Speech, F. Dellaert, Proceedings of the ICSLP '96, October, 1996. – Try a lots of method and use combined one. Emotion Recognition and Its Application to Computer Agents with Spontaneous Interactive Capabilities - Ryohei Nakatsu, Joy Nicholson and Naoko Tosa – Using Neural network

6. „Our” problem Smiling faces. Input : a set of photos of the not same person with different face expressions and the information that some of them are smiling faces Task : to write a program (with SVM) recognizing the smiling faces (on video) of the not same person Output : smiling or not, and the statistics of the implemented method.

7. The SVM Support Vector Learning

8. Our Solution 1.step We need lots of pictures: 2. Step Processing the pictures

9. Our Solution 17x17 22x22 28x28 36x36

10. Our Solution 4. Input : video file detect face(s) detect emotion

11. „Future” Work – TO DO What we wanted to do, but we have not enough time…

12. Tesekkurler Thanks for your attention Köszönöm a figyelmet Danke schön Vã multumesc foarte mult!