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Fast Face Detection Based on AdaBoost and Canny Operators

机译:基于Adaboost和Canny运算符的快速面检测

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Detection speed of traditional face detection method based on AdaBoost algorithm is slow since AdaBoost asks a large number of features. Therefore, to address this shortcoming, we proposed a fast face detection method based on AdaBoost and canny operators in this paper. Firstly, we use canny operators to detect edge of face image which separates the region of the possible human face from image, and then do face detection in the separated region using Modest AdaBoost algorithm (MAB). Before using MAB to achieve face detection, utilizing canny operators to detect edge can make this algorithm effectively filter information, retain useful information, reduce the amount of information and improve detection speed. Experimental results show that the algorithm can obtain higher detection accuracy and detection speed has been significantly improved at the same time.
机译:由于adaboost询问了大量功能,基于Adaboost算法的传统面部检测方法的检测速度很慢。因此,为了解决这种缺点,我们提出了一种基于本文Adaboost和Canny Operator的快速面检测方法。首先,我们使用Canny Operators检测面部图像的边缘,其将可能的人面的区域与图像分开,然后使用适度的Adaboost算法(MAB)在分离区域中进行面部检测。在使用MAB实现面部检测之前,利用Canny运算符来检测边缘可以使该算法有效地滤波信息,保留有用的信息,减少信息量并提高检测速度。实验结果表明,该算法可以获得更高的检测精度,检测速度同时显着提高。

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