Detail publikace

Evolutionary Approximation of Gradient Orientation Module in HOG-based Human Detection System

WIGLASZ, M. SEKANINA, L.

Originální název

Evolutionary Approximation of Gradient Orientation Module in HOG-based Human Detection System

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

The histogram of oriented gradients (HOG) feature extraction is a computer vision method widely used in embedded systems for detection of objects such as pedestrians. We used Cartesian genetic programming (CGP) to exploit the error resilience in the HOG algorithm. We evolved new approximate implementations of the arctan function, which is typically employed to compute the gradient orientations. When the best evolved approximations are integrated into the SW implementation of the HOG algorithm, not only the execution time, but also the classification accuracy was improved in comparison with the accurate implementation and the state-of-the-art approximate implementations.

Klíčová slova

Functional approximation, Cartesian genetic programming, Histogram of oriented gradients

Autoři

WIGLASZ, M.; SEKANINA, L.

Vydáno

14. 11. 2017

Nakladatel

IEEE Signal Processing Society

Místo

Montreal

ISBN

978-1-5090-5989-8

Kniha

2017 IEEE Global Conference on Signal and Information Processing GlobalSIP 2017

Strany od

1300

Strany do

1304

Strany počet

5

URL

https://www.fit.vut.cz/research/publication/11441/

BibTex

@inproceedings{BUT144438,
  author="Michal {Wiglasz} and Lukáš {Sekanina}",
  title="Evolutionary Approximation of Gradient Orientation Module in HOG-based Human Detection System",
  booktitle="2017 IEEE Global Conference on Signal and Information Processing GlobalSIP 2017",
  year="2017",
  pages="1300--1304",
  publisher="IEEE Signal Processing Society",
  address="Montreal",
  doi="10.1109/GlobalSIP.2017.8309171",
  isbn="978-1-5090-5989-8",
  url="https://www.fit.vut.cz/research/publication/11441/"
}