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Proceedings Paper

HOG pedestrian detection based on edge symmetry and trilinear interpolation
Author(s): Dandan Wang; Tongei Lu; Yanduo Zhang
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Paper Abstract

In computer vision, pedestrian detection is a key problem. In this paper, we propose to speed up the HOG+SVM algorithm without sacrificing the classification accuracy. In order to eliminate the effects of aliasing phenomenon that products in the process of HOG extraction, we used trilinear interpolation to extract feature. This paper proposed HOG pedestrian detection method based on edge symmetry. In these experiments, we used INRIA dataset. Traditional HOG pedestrian detection is presence of slow detection speed and low detection rate. Experiments show that using trilinear interpolation and edge symmetry not only can improve the detection effect, but also can improve the detection rate.

Paper Details

Date Published: 8 March 2018
PDF: 7 pages
Proc. SPIE 10609, MIPPR 2017: Pattern Recognition and Computer Vision, 1060907 (8 March 2018); doi: 10.1117/12.2282815
Show Author Affiliations
Dandan Wang, Wuhan Institute of Technology (China)
Hubei Provincial Key Lab. of Intelligent Robot (China)
Tongei Lu, Wuhan Institute of Technology (China)
Hubei Provincial Key Lab. of Intelligent Robot (China)
Yanduo Zhang, Wuhan Institute of Technology (China)
Hubei Provincial Key Lab. of Intelligent Robot (China)


Published in SPIE Proceedings Vol. 10609:
MIPPR 2017: Pattern Recognition and Computer Vision
Zhiguo Cao; Yuehuang Wang; Chao Cai, Editor(s)

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