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Human silhouette identification based on Gabor feature and convolutional neural network(PDF)


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Human silhouette identification based on Gabor feature and convolutional neural network
Wang LinDong Nan
School of Automation and Information Engineering,Xi’an University of Technology,Xi’an 710048,China
human silhouette identification Gabor feature convolutional neural network picture processing deep learning VOC2012 data set
Traditional methods can not divide the human silhouette accurately in a single image. Aiming at this problem,a method of human silhouette extraction based on Gabor feature and convolutional neural network(CNN)is proposed. Firstly the Gabor wavelet feature of human image in 8 directions is calculated and introduced into the improved CNN for the character model training; secondly the being-tested image is introduced into character model for detection after calculating Gabor wavelet feature,and the mask of the characters is output; finally the mask is processed by morphology and an operation is made with the original image to get the human silhouette. The detection accuracy of this method is up to 96% in the test of VOC2012 data set. The experimental results show that the combination of traditional feature extraction method and the feature learning method of deep learning improves the speed of feature learning and the detection accuracy.


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Last Update: 2018-02-28