@inproceedings{oai:kyutech.repo.nii.ac.jp:00005027,
 author = {Nakashima, Yuuki and Tan, Joo kooi and タン, ジュークイ and Kim, Hyungseop and 金, 亨燮 and 石川, 聖二 and Ishikawa, Seiji},
 book = {2014 Joint 7th International Conference on Soft Computing and Intelligent Systems (SCIS) and 15th International Symposium on Advanced Intelligent Systems (ISIS)},
 month = {Feb},
 note = {Development of an ITS (Intelligent Transport System) has drawn much attention from computer vision community in recent years. In particular, various techniques for detecting pedestrians automatically have been proposed by many researchers. Among them, the HOG feature proposed by Dalai & Triggs has gained much interest in the pedestrian detection. However, previous methods including the original HOG feature have not achieved satisfactory detection rates. In this paper, we propose an extension of the HOG feature, i.e., flexible choice of the number of bins and automatic definition of a cell size and a block size by parameterizing their scales. By comparative experiments, it was confirmed that the proposed method outperforms the previous methods in the performance of pedestrian detection., SCIS & ISIS 2014, December 3-6, 2014, Kitakyushu International Conference Center},
 pages = {1198--1202},
 publisher = {IEEE},
 title = {A pedestrian detection method using the extension of the HOG feature},
 year = {2015},
 yomi = {イシカワ, セイジ}
}