60 likes | 82 Views
Explore advanced classifiers like Ridge Regression and SNoW for better face detection. Learn to apply AdaBoost for feature selection and enhanced results in your projects.
E N D
A simple classifier • Ridge regression • A variation on standard linear regression • Adds a “ridge” term that has the effect of “smoothing” the weights • Equivalent to training a linear network with weight decay.
A “Strong” Classifier:SNoW– Sparse Network of Winnows • Roth et al. 2000 – Currently best reported face detector • 1. Turn each pixel into a sparse, binary vector • 2. Activation = sign( ) • 3. Train with the Winnow update rule
AdaBoost for Feature Selection • Viola and Jones (2001) used AdaBoost as a feature selection method • For each round of AdaBoost: • For each patch, train a classifier using only that one patch. • Select the best one as the classifier for this round • reweight distribution based on that classifier.