Adam Yeh

1. Adam Yeh UCF Computer Vision REU Week 6

2. About Me • Cornell University, • Major: Computer Science • Minor: Mathematics • Rising Junior • Hometown: Oviedo • Goals: • Grad school-Ph.D? Math/CS • Research career… • This is why I’m here…

3. Motivation • 7 basic facial expressions • Given face, classify into correct facial expression • Bartlett et al., CVPR 2005 • Used Adaboost for feature selection, then SVM for classification • Achieved >90% correct classification

4. This Week • Combined code for AdaSVM • LibSVM package + existing Adaboost code • Run Adaboost to find 300 features • Use these feature values as input vector for SVM • Ran code on AdaSVM • First on Faces vs Non Faces • Facial Expressions • Interesting Results

5. Facial Recognition • 78% - AdaSVM, radial basis • 72% - AdaSVM, linear basis • 77% - SVM, radial basis

6. Facial Expressions • Binary Classification: One expression vs. another • Happy vs Neutral • 54% svm, radial basis • 59% AdaSVM, radial basis • 61% svm, linear basis • 47% AdaSVM, linear basis

7. Facial Expressions cont. • Surprise vs Neutral • 52% svm, radial basis • 60% AdaSVM, radial basis • 51% svm, linear basis • 51% AdaSVM, linear basis • Happy vs Surprise • 69% svm, radial basis • 68% AdaSVM, radial basis • 79% svm, linear basis • 65% AdaSVM, linear basis

8. Next Week • Finish expression vs expression testing • One vs. all testing • Eventually, combine results to create one system that determines facial expression