Abstract: Human detection system using Histogram of Oriented Gradients (HOG) feature and AdaBoost classifier (HOG-AdaBoost) in FPGA ALTERA DE2-115 are presented in this paper. This work is expanded version from our previous study. This paper discusses 1) the HOG performance in detecting human from a passive images with other point-of-views (30 deg., 40 deg., 50 deg., 60 deg. and up to 70 deg.); 2) FPS test with various image sizes (320 x 240, 640 x 480, 800 x 600, and 1280 x 1024); 3) re-measurement the FPGA’s power consumption and 4) simulate the architecture in RTL. We used three databases as a parameter for test purpose, i.e. INRIA, MIT, and Daimler.

Trio Adiono Adiono, Kevin Shidqi Prakoso, Christoporus Deo Putratama, Bramantio Yuwono and Syifaul Fuada, “HOG-AdaBoost Implementation for Human Detection Employing FPGA ALTERA DE2-115” International Journal of Advanced Computer Science and Applications(IJACSA), 9(10), 2018. http://dx.doi.org/10.14569/IJACSA.2018.091042

@article{Adiono2018,
title = {HOG-AdaBoost Implementation for Human Detection Employing FPGA ALTERA DE2-115},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2018.091042},
url = {http://dx.doi.org/10.14569/IJACSA.2018.091042},
year = {2018},
publisher = {The Science and Information Organization},
volume = {9},
number = {10},
author = {Trio Adiono Adiono and Kevin Shidqi Prakoso and Christoporus Deo Putratama and Bramantio Yuwono and Syifaul Fuada}
}