Computer Science ›› 2016, Vol. 43 ›› Issue (6): 308-311.doi: 10.11896/j.issn.1002-137X.2016.06.061

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Pedestrian Detection Based on PCA Dimension Reduction of Multi-feature Cascade

GAN Ling, ZOU Kuan-zhong and LIU Xiao   

  • Online:2018-12-01 Published:2018-12-01

Abstract: In pedestrian detection,Histogram of oriented gradient(HOG) has the defects of too much redundant information,low detection speed,this paper proposed features cascading pedestrian detection based on PCA dimensional reduction.Firstly,we used PCA to reduce the dimension of HOG features,then took HOG features,Gabor features and color features as the features of pedestrian detection.Finally we used SVM radial basis (RBF) kernel function to classify.Experiments on INRIA pedestrian database show that this method not only increases the speed of classification,but also improve the accuracy of detection.

Key words: Pedestrian detection,Histogram of oriented gradient(HOG),Radial basis kernel function(RBF)

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