Proceedings of the 3rd Workshop on Advanced Research and Technology in Industry (WARTIA 2017)

Convolution Pedestrian Detection Based on Random Fusion of Color and Gradient

Authors
Xiangquan Gui, Jiajun Jiang, Li Li, Dongmei Chen, Lei Gao
Corresponding Author
Xiangquan Gui
Available Online November 2017.
DOI
10.2991/wartia-17.2017.6How to use a DOI?
Keywords
double color; channel switching; extended operator; random fusion;
Abstract

The complex prospects in pedestrian detection, such as backpacks and other obstacles, are likely to cause interference to pedestrians. Since previous pedestrian detection can only use separate gradient information, the color information is neglected, and the gradient direction information is not accurate because of noise. In this paper, we propose a convolution network based on the combination of double color and improved Sobel extended gradient information to detect pedestrians and other prospects. The model combines convolution of RGB and HSI color channels and improved Sobel extended gradient fusion channels respectively. Then the stochastic fusion feature vector method is proposed to fuse the color and gradient information randomly, and the final result of pedestrian detection is obtained. Experimental results show that the proposed method improves the detection accuracy.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 3rd Workshop on Advanced Research and Technology in Industry (WARTIA 2017)
Series
Advances in Engineering Research
Publication Date
November 2017
ISBN
10.2991/wartia-17.2017.6
ISSN
2352-5401
DOI
10.2991/wartia-17.2017.6How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Xiangquan Gui
AU  - Jiajun Jiang
AU  - Li Li
AU  - Dongmei Chen
AU  - Lei Gao
PY  - 2017/11
DA  - 2017/11
TI  - Convolution Pedestrian Detection Based on Random Fusion of Color and Gradient
BT  - Proceedings of the 3rd Workshop on Advanced Research and Technology in Industry (WARTIA 2017)
PB  - Atlantis Press
SP  - 26
EP  - 34
SN  - 2352-5401
UR  - https://doi.org/10.2991/wartia-17.2017.6
DO  - 10.2991/wartia-17.2017.6
ID  - Gui2017/11
ER  -