Publication Details
Evolutionary Approximation of Gradient Orientation Module in HOG-based Human Detection System
Sekanina Lukáš, prof. Ing., Ph.D. (DCSY)
Functional approximation, Cartesian genetic programming, Histogram of oriented
gradients
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.
@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/"
}