| アイテムタイプ |
学術雑誌論文 = Journal Article(1) |
| 公開日 |
2024-02-05 |
| 資源タイプ |
|
|
資源タイプ識別子 |
http://purl.org/coar/resource_type/c_6501 |
|
資源タイプ |
journal article |
| タイトル |
|
|
タイトル |
Hardware-oriented Algorithm for Human Detection using GMM-MRCoHOG Features |
|
言語 |
en |
| 言語 |
|
|
言語 |
eng |
| 著者 |
Takemoto, Ryogo
Nagamine, Yuya
Yoshihiro, Kazuki
Shibata, Masatoshi
Yamada, Hideo
田中, 悠一朗
榎田, 修一
田向, 権
|
| 抄録 |
|
|
内容記述タイプ |
Abstract |
|
内容記述 |
In this research, we focus on Gaussian mixture model-multiresolution co-occurrence histograms of oriented gradients (GMM-MRCoHOG) features using luminance gradients in images and propose a hardware-oriented algorithm of GMM-MRCoHOG to implement it on a field programmable gate array (FPGA). The proposed method simplifies the calculation of luminance gradients, which is a high-cost operation in the conventional algorithm, by using lookup tables to reduce the circuit size. We also designed a human-detection digital architecture of the proposed algorithm for FPGA implementation using high-level synthesis. The verification results showed that the processing speed of the proposed architecture was approximately 123 times faster than that of the FPGA implementation of VGG-16. |
|
言語 |
en |
| 備考 |
|
|
内容記述タイプ |
Other |
|
内容記述 |
17th International Conference on Computer Vision Theory and Applications, 6-8 February, 2022, Online Streaming |
|
言語 |
en |
| 書誌情報 |
en : Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications VISIGRAPP
p. 749-757,
発行日 2022
|
| 出版社 |
|
|
出版者 |
ScitePress |
| DOI |
|
|
|
識別子タイプ |
DOI |
|
|
関連識別子 |
https://doi.org/10.5220/0010848100003124 |
| ISBN |
|
|
|
識別子タイプ |
ISBN |
|
|
関連識別子 |
978-989-758-555-5 |
| ISSN |
|
|
収録物識別子タイプ |
EISSN |
|
収録物識別子 |
2184-4321 |
| 著作権関連情報 |
|
|
権利情報Resource |
https://creativecommons.org/licenses/by-nc-nd/4.0/ |
|
権利情報 |
CC BY-NC-ND 4.0 |
| 出版タイプ |
|
|
出版タイプ |
VoR |
|
出版タイプResource |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
| 査読の有無 |
|
|
値 |
yes |
| 研究者情報 |
|
|
URL |
https://hyokadb02.jimu.kyutech.ac.jp/html/100001426_ja.html |
10428634.pdf (4.1 MB)
