@inproceedings{25ed84aa0faa43c4bb0cc1c5541229bb,
title = "Pedestrian detection using hog-based block selection",
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.",
keywords = "Camera, Computer Vision, HOG, Intelligent Vehicle, Pedestrian Detection",
author = "Minsung Kang and Lim, {Young Chul}",
year = "2014",
doi = "10.5220/0005147607830787",
language = "English",
series = "ICINCO 2014 - Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics",
publisher = "SciTePress",
pages = "783--787",
editor = "Joaquim Filipe and Joaquim Filipe and Oleg Gusikhin and Kurosh Madani and Jurek Sasiadek",
booktitle = "ICINCO 2014 - Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics",
note = "11th International Conference on Informatics in Control, Automation and Robotics, ICINCO 2014 ; Conference date: 01-09-2014 Through 03-09-2014",
}