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Face detection in complex background based on Adaboost algorithm and YCbCr skin color model

机译:基于Adaboost算法和YCbCr肤色模型的复杂背景人脸检测

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Face detection is a fundamental and important research theme in the topic of Pattern Recognition and Computer Vision. Now, remarkable fruits have been achieved. Among these methods, statistics based methods hold a dominant position. In this paper, Adaboost algorithm based on Haar-like features is used to detect faces in complex background. The method combining YCbCr skin model detection and Adaboost is researched, the skin detection method is used to validate the detection results obtained by Adaboost algorithm. It overcomes false detection problem by Adaboost. Experimental results show that nearly all non-face areas are removed, and improve the detection rate.
机译:人脸检测是模式识别和计算机视觉主题中的一项基本且重要的研究主题。现在,已经取得了令人瞩目的成果。在这些方法中,基于统计的方法占据主导地位。本文采用基于Haar样特征的Adaboost算法来检测复杂背景下的人脸。研究了YCbCr皮肤模型检测与Adaboost相结合的方法,该皮肤检测方法用于验证Adaboost算法获得的检测结果。它克服了Adaboost的错误检测问题。实验结果表明,几乎所有的非面部区域都被去除,并提高了检测率。

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