Computer Science ›› 2017, Vol. 44 ›› Issue (Z11): 221-224.doi: 10.11896/j.issn.1002-137X.2017.11A.046

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Pedestrian Detection Based on DCT of Multi-channel Feature

LIU Chun-yang, WU Ze-min, HU Lei and LIU Xi   

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

Abstract: In pedestrian detection,multi-channel feature detection has the defect of incomplete using features.In this paper,an algorithm of multi-channel feature detection based on discrete cosine transform (DCT) was proposed.We used a two-layer convolution network for arranging the image information after DCT to build a new channel in the frequency domain.This channel can describe complex textures about pedestrian.Combined with the features of the histogram of gradient and the color space as well as the DCT frequency domain,a low cost multi-channel pedestrian detector has been trained based on the Adaboost algorithm.Experiments on popular pedestrian databases show that the proposed method improves the accuracy of detection,and the effect is remarkable in low false positive per image.

Key words: Pedestrian detection,DCT,Multi-channel feature

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