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Face Detection Based on Facial Features and Linear Support Vector Machines

机译:基于面部特征和线性支持向量机的人脸检测

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Face detection is a complicated and significant problem in pattern recognition and has wide application. This paper proposes a fast face detection algorithm based on facial features and linear Support Vector Machines (LSVM). First, using of skin color information, the algorithm quickly excludes most background regions from the images primarily leaving the skin color regions. Then we use LSVM to separate more non-face regions from the remaining regions, for exiting big differences between the face regions and non-face regions. Finally, we identify the face candidates by detecting eyes and mouth. The experimental results demonstrate that the algorithm can further improve the detection accuracy and lower false detection rate and greatly speed up the detection rate.
机译:人脸检测是模式识别中一个复杂而重要的问题,具有广泛的应用前景。本文提出了一种基于面部特征和线性支持向量机(LSVM)的快速人脸检测算法。首先,使用肤色信息,该算法可以从图像中快速排除大部分背景区域,而这些背景区域主要是离开肤色区域的。然后,我们使用LSVM从其余区域中分离出更多的非面部区域,以消除面部区域与非面部区域之间的巨大差异。最后,我们通过检测眼睛和嘴巴来识别人脸候选对象。实验结果表明,该算法可以进一步提高检测精度,降低误检率,大大提高了检测率。

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