Hardware-Oriented Algorithm for Human Detection using GMM-MRCoHOG Features
| Autor: | Ryogo Takemoto, Yuya Nagamine, Kazuki Yoshihiro, Masatoshi Shibata, Hideo Yamada, Yuichiro Tanaka, Shuichi Enokida, Hakaru Tamukoh |
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| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. 4:749-757 |
| Popis: | 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. 17th International Joint Conference on Computer Vision Theory and Applications (VISAPP 2022), February 6-8, 2022, Online Streaming |
| Databáze: | OpenAIRE |
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