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Research on human face location based on Adaboost and convolutional neural network

机译:基于Adaboost和卷积神经网络的人脸定位研究

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To increase speed and accuracy of human face location with Adaboost algorithm, this article proposes a human face location method combining Adaboost with convolutional neural network (CNN). This method firstly uses CNN algorithm to carry out human face training, then applies Gaussian mixture model to establish a background and gets moving targets through background subtraction before making a rough localization by Adaboost in moving targets area and precise location by CNN algorithm. Experimental results show that: this method is superior to Adaboost algorithm in the aspect of human face location speed and accuracy.
机译:为了利用Adaboost算法提高人脸定位的速度和准确性,本文提出了一种将Adaboost与卷积神经网络(CNN)相结合的人脸定位方法。该方法首先使用CNN算法进行人脸训练,然后应用高斯混合模型建立背景并通过背景减法获得运动目标,然后由Adaboost对运动目标区域进行粗略定位,并通过CNN算法进行精确定位。实验结果表明:该方法在人脸定位速度和准确性方面优于Adaboost算法。

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