A hardware-oriented algorithm of GMM-MRCoHOG for high-performance human detection by an FPGA

Yuya Nagamine; Kazuki Yoshihiro; Masatoshi Shibata; Hideo Yamada; Shuichi Enokida; Hakaru Tamukoh

doi:10.1117/12.2591024

13 March 2021 A hardware-oriented algorithm of GMM-MRCoHOG for high-performance human detection by an FPGA

Yuya Nagamine, Kazuki Yoshihiro, Masatoshi Shibata, Hideo Yamada, Shuichi Enokida, Hakaru Tamukoh

Proceedings Volume 11766, International Workshop on Advanced Imaging Technology (IWAIT) 2021; 117660B (2021) https://doi.org/10.1117/12.2591024
Event: International Workshop on Advanced Imaging Technology 2021 (IWAIT 2021), 2021, Online Only

Abstract

In this study, we propose a hardware-oriented Gaussian mixture model – multiresolution co-occurrence histograms of oriented gradients (GMM–MRCoHOG) algorithm for efficient human detection by a field-programmable gate array (FPGA). GMM–MRCoHOG is a HOG-based human detection method in which the computation of angles is quantized to 36 directions and 2D Gaussian distribution computation causes a decrease in processing speed and an increase in hardware resource usage. We propose a hardware-oriented algorithm to solve these problems. First, we propose a rough angle computation method of comparison with a tangent table. Second, we propose a bit-shifting-based Gaussian distribution computation method. Experimental results show that the proposed hardware-oriented algorithm does not significantly reduce the detection accuracy of GMM–MRCoHOG. High-level synthesis results of the FPGA implementation show that fast, low-resource processing is possible.

Citation Download Citation

Yuya Nagamine, Kazuki Yoshihiro, Masatoshi Shibata, Hideo Yamada, Shuichi Enokida, and Hakaru Tamukoh "A hardware-oriented algorithm of GMM-MRCoHOG for high-performance human detection by an FPGA", Proc. SPIE 11766, International Workshop on Advanced Imaging Technology (IWAIT) 2021, 117660B (13 March 2021); https://doi.org/10.1117/12.2591024

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