Multi-View Face Detection Based on AdaBoost and Skin Color

Peng Deng, Mingtao Pei
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引用次数: 15

Abstract

This paper describes a multi-view face detection method which combined skin color information and AdaBoost-based face detection technique together to improve the detection accuracy and detection speed. First the input image is converted into YCbCr color space, then the image is binarized according to skin threshold and a binary image was obtained in which pixels with value 1 are skin-pixels and pixels with value 0 are non-skin pixels. After that only the skin regions are scanned by multi-AdaBoost detectors which were also trained on skin binarized face images. Before scanned by the multi-AdaBoost detectors, the sub windows are filtered by the ratio of the skin- pixels in the sub windows which can eliminate most of the false face regions .The experimental results show that the proposed method can achieve high detection accuracy with fast detection speed.
基于AdaBoost和肤色的多视角人脸检测
本文介绍了一种将肤色信息与基于adaboost的人脸检测技术相结合的多视图人脸检测方法,提高了检测精度和检测速度。首先将输入图像转换为YCbCr色彩空间,然后根据皮肤阈值对图像进行二值化,得到值为1的像素为皮肤像素,值为0的像素为非皮肤像素的二值图像。之后,多个adaboost检测器只扫描皮肤区域,这些检测器也对皮肤二值化的人脸图像进行了训练。在多adaboost检测器扫描前,对子窗口进行皮肤像素比滤波,消除了大部分假人脸区域,实验结果表明,该方法具有较高的检测精度和较快的检测速度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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