Face Detection Based on Feature Tailoring and Skin Color Space
College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China
This paper is used to solve the time-consuming problem of training samples in Adaboost algorithm and propose an improved FTAdaboost algorithm based on feature tailoring. In the beginning, this paper is used to make all samples have the same weight, train them once and tailor the features before the first reflection point of the error rate curve which have high error rate and poor classification ability, then reduce the number of samples and save training time. According to the distribution of facial organs, the algorithm determines whether the specified area meets the characteristics of skin-color space, then eliminates the influence of wrong facial images. The experimental results show that the algorithm based on feature tailoring can shorten the training time significantly and the detection with the skin-color space can decrease the error rate to some extent.
Key words: fatigue detection / FTAdaboost / classifier / skin color space
© Owned by the authors, published by EDP Sciences, 2015
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