Cooperative Coevolutionary Approximation in HOG-based Human Detection Embedded System
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F18%3APU130715" target="_blank" >RIV/00216305:26230/18:PU130715 - isvavai.cz</a>
Result on the web
<a href="https://www.fit.vut.cz/research/publication/11695/" target="_blank" >https://www.fit.vut.cz/research/publication/11695/</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/SSCI.2018.8628910" target="_blank" >10.1109/SSCI.2018.8628910</a>
Alternative languages
Result language
angličtina
Original language name
Cooperative Coevolutionary Approximation in HOG-based Human Detection Embedded System
Original language description
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 cooperative coevolutionary Cartesian genetic programming (CGP) to exploit the error resilience in the HOG algorithm. We evolved new approximate implementations of the arctan and square root functions, which are typically employed to compute the gradient orientations and magnitudes. When the best evolved approximations are integrated into the software implementation of the HOG algorithm, not only the execution time, but also the classification accuracy was improved in comparison with approximations evolved separately using CGP and also compared to the state-of-the art approximate implementations. As the evolved code does not contain any loops and branches, it is suitable for the follow-up low-power hardware implementation.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2018 IEEE Symposium Series on Computational Intelligence (SSCI 2018)
ISBN
978-1-5386-9276-9
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
1313-1320
Publisher name
Institute of Electrical and Electronics Engineers
Place of publication
Bengaluru
Event location
Bengaluru
Event date
Nov 18, 2018
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000459238800180