Computer Science ›› 2018, Vol. 45 ›› Issue (6A): 210-214.

• Pattern Recognition & Image Processing • Previous Articles     Next Articles

Pedestrian Detection Based on Objectness and Sapce-Time Covariance Features

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

  1. College of Communications Engineering,PLAUST,Nanjing 210007,China
  • Online:2018-06-20 Published:2018-08-03

Abstract: In order to solve the fusion of space-time information and excessive detection area in pedestrian detection,a pedestrian detection method was proposed based on objectness and space-time covariance features.Firstly,binarized normed gradients algorithm is used for a test image to get objectness evaluations,and a pedestrian detection candidate area is formed.Secondly,the spatial and temporal features are extracted.Finally,a space-time detector based on cova-riance information was proposed to improve the accuracy.Experimental results on the INRIA and Caltech demonstrate that the proposed method outperforms the state-of-art pedestrian detectors in accuracy.

Key words: Computer vision, Covariance features, Objectness, Pedestrian detection

CLC Number: 

  • TP391
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