Pedestrian Detection using HOG-based Block Selection

Minsung Kang, Young Chul Lim

2014

Abstract

Recently, pedestrian detection methods have been popularly used in the field of intelligent vehicles. In most previous works, the Histogram of Oriented Gradients (HOG) is used to extract features for pedestrian detection. However HOG is difficult to use in the real-time operating system of an intelligent vehicle. In this paper, we proposed a pedestrian detection method using a HOG-based block selection. First, we analyse the HOG block and select the parts of the block with a high hit rate. We then use only 20% of the total HOG blocks for the pedestrian feature. The proposed method is 5 times faster than methods using the entire feature, while performance remains almost the same.

Paper Citation

in Harvard Style

Kang M. and Lim Y. (2014). Pedestrian Detection using HOG-based Block Selection . In Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics - Volume 2: IVC&ITS, (ICINCO 2014) ISBN 978-989-758-040-6, pages 783-787. DOI: 10.5220/0005147607830787

in Bibtex Style

@conference{ivc&its14,
author={Minsung Kang and Young Chul Lim},
title={Pedestrian Detection using HOG-based Block Selection},
booktitle={Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics - Volume 2: IVC&ITS, (ICINCO 2014)},
year={2014},
pages={783-787},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005147607830787},
isbn={978-989-758-040-6},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics - Volume 2: IVC&ITS, (ICINCO 2014)
TI - Pedestrian Detection using HOG-based Block Selection
SN - 978-989-758-040-6
AU - Kang M.
AU - Lim Y.
PY - 2014
SP - 783
EP - 787
DO - 10.5220/0005147607830787