Hardware-oriented Algorithm for Human Detection using GMM-MRCoHOG Features

Ryogo Takemoto, Yuya Nagamine, Kazuki Yoshihiro, Masatoshi Shibata, Hideo Yamada, Yuichiro Tanaka, Shuichi Enokida, Hakaru Tamukoh, Hakaru Tamukoh

2022

Abstract

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.

Paper Citation

in Harvard Style

Takemoto R., Nagamine Y., Yoshihiro K., Shibata M., Yamada H., Tanaka Y., Enokida S. and Tamukoh H. (2022). Hardware-oriented Algorithm for Human Detection using GMM-MRCoHOG Features. In Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP; ISBN 978-989-758-555-5, SciTePress, pages 749-757. DOI: 10.5220/0010848100003124

in Bibtex Style

@conference{visapp22,
author={Ryogo Takemoto and Yuya Nagamine and Kazuki Yoshihiro and Masatoshi Shibata and Hideo Yamada and Yuichiro Tanaka and Shuichi Enokida and Hakaru Tamukoh},
title={Hardware-oriented Algorithm for Human Detection using GMM-MRCoHOG Features},
booktitle={Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP},
year={2022},
pages={749-757},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010848100003124},
isbn={978-989-758-555-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP
TI - Hardware-oriented Algorithm for Human Detection using GMM-MRCoHOG Features
SN - 978-989-758-555-5
AU - Takemoto R.
AU - Nagamine Y.
AU - Yoshihiro K.
AU - Shibata M.
AU - Yamada H.
AU - Tanaka Y.
AU - Enokida S.
AU - Tamukoh H.
PY - 2022
SP - 749
EP - 757
DO - 10.5220/0010848100003124
PB - SciTePress