Learning and Vision: Discriminative Models. Paul Viola Microsoft Research email@example.com. Overview. Perceptrons Support Vector Machines Face and pedestrian detection AdaBoost Faces Building Fast Classifiers Trading off speed for accuracy… Face and object detection
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The linear program can return any multiple of the correct
Slack variables & Weight prior
- Force the solution toward zero
with zero margin
Enforces a non-zero
margin between examples
and the decision boundary.
First Fast System
- Low Res to Hi
Similar to Haar wavelets
Papageorgiou, et al.
Unique Binary Features
A classifier with 200 rectangle features was learned using AdaBoost
95% correct detection on test set with 1 in 14084
Not quite competitive...
ROC curve for 200 feature classifier
Facial Feature Localization
Good Features beat Good Learning
Learning beats No Learning