Abstract:

The framework of the inherited boosting learning methods is proposed based on “heredity plus variation” inheriting pattern, which can train four sorts of cascade classifiers. Besides the two traditional cascade classifiers, namely basic cascade classifiers based on “no heredity” inheriting pattern and chained cascade classifiers based on “full heredity” inheriting pattern, there are two new ones, which are feature inherited cascade classifiers and weak classifiers inherited cascade classifiers both based on “partly heredity plus partly variation” inheriting pattern. Although the new ones both have some extra costs, they have better fitting, can balance properly between the convergent speed and the generalization ability and thus outperform the traditional ones. Experimental results on upright frontal face detection based on Real AdaBoost, Gentle AdaBoost and LUT weak classifiers confirm the effectiveness of the new inherited boosting learning methods.

Key words: chained boosting learning;embedded cascade classifier;inherited boosting learning;inherited cascade classifier;LUT weak classifier;face detection