Well from what I understand, AdaBoost is more like a framework to combine multiple weak classifiers. The idea being many weak classifiers, maybe be geared for different parts, like eyes, lips etc, and combination of them is better than a single strong classifier. For AdaBoost the problem becomes of selecting what weak classifiers to use e.g. Haar-like features, maybe something with wavelets, Gabor features, histograms etc.
I guess this is something to keep in mind when plug-in is at that stage.
Well from what I understand, AdaBoost is more like a framework to combine multiple weak classifiers. The idea being many weak classifiers, maybe be geared for different parts, like eyes, lips etc, and combination of them is better than a single strong classifier. For AdaBoost the problem becomes of selecting what weak classifiers to use e.g. Haar-like features, maybe something with wavelets, Gabor features, histograms etc.
I guess this is something to keep in mind when plug-in is at that stage.