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Research on an improved algorithm of face detection based on skin color features and cascaded Ada Boost

机译:基于肤色特征和级联Ada Boost的改进人脸检测算法研究

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The paper presents an improved algorithm in face detection that combines the YcbCr color space to detect the skin region and the AdaBoost algorithm to precise detection. The Ada Boost algorithm is one technique among the most successful algorithms in face detection, but in view of its time costs and high false acceptance rate, the paper proposes a two-stage detection method based on skin color segmentation which has relatively high speed of operation at the expense of accuracy and the cascaded AdaBoost algorithm which has high accuracy in face detection but time consuming. Here the modified algorithm research uses the open source platform Open Cv to simulate. The result shows the algorithm is more capable for real-time face detection.
机译:本文提出了一种改进的人脸检测算法,该算法结合了YcbCr颜色空间来检测皮肤区域,并结合了AdaBoost算法来进行精确检测。 Ada Boost算法是人脸检测中最成功的算法之一,但鉴于其时间成本和较高的错误接受率,本文提出了一种基于肤色分割的两阶段检测方法,该方法具有较高的运算速度以准确性为代价,并采用级联的AdaBoost算法,该算法在人脸检测中具有很高的准确性,但是很耗时。在这里,改进的算法研究使用开源平台Open Cv进行仿真。结果表明,该算法具有更强的实时人脸检测能力。

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