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Yes, the AdaBoosting algorithm is used for Haar based Classifier training.
Essentially we combine weak classifiers into our classifier cascade to hopefully form a strong learner, by way of boosting.
AdaBoosting algorithm (aka Adaptive Boosting)
This algorithm was initially proposed by Yoav Freund and Robert Schapire in A Decision-Theoretic Generalization of on-Line Learning and an Application to Boosting. It is used to improve a learning algorithms performance, by calling weak classifiers repeatedly and updating weights.
Hence you will find these boosted classifer parameters to choose from for your opencv_traincascade utility:
-bt <{DAB, RAB, LB, GAB(default)}>
DAB - Discrete AdaBoost, RAB - Real AdaBoost, LB - LogitBoost, GAB - Gentle AdaBoost.
