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Adam Yeh. UCF Computer Vision REU Week 8. Problems. Fixed bug in SVM code Data had to be normalized for better results Faces/non-faces improved from 75% to 95%. Finding Poles. Recap: Run all binary SVMs (6 classes -> 15 binary SVMs)
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Adam Yeh UCF Computer Vision REU Week 8
Problems • Fixed bug in SVM code • Data had to be normalized for better results • Faces/non-faces improved from 75% to 95%
Finding Poles • Recap: • Run all binary SVMs (6 classes -> 15 binary SVMs) • For each class, find the intersection of non-SVs from binary SVMs • Progress: • Ran on training of about 50 images/class • Found poles on all but one class • Need metric to measure “closeness” to a pole
Finding Poles • Happy • Sad
Finding Poles • Anger • Surprise
Finding Poles • Disgust
Database Expansion • Database • Shift image left, right, up, down • Rotate image by small degree • Modify intensities • Blur images • Scale images up and down • Apply Gaussian filters in different regions • For each image, generates 200 images
Database Expansion • Testing: Anger vs Disgust • Radial Basis SVM: 73% vs 52% on testing • Linear Basis SVM: 54% vs 65% on testing • Problem • Previous algorithm will break down if binary classifications do not yield good results
Next Week • Verify binary SVM results with larger database • Experiment with eliminating certain transformations from database • Manual one vs. all binary SVM • Switch to CoreSVM • libSVM runs ~1hr per binary SVM • Debug code • Verify SVMs are more confused