Detection and modeling of alcohol intoxication dynamic from IR images based on clustering driven by ABC algorithm

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F19%3A10242728" target="_blank" >RIV/61989100:27240/19:10242728 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007/978-3-030-28377-3_32" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-030-28377-3_32</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-28377-3_32" target="_blank" >10.1007/978-3-030-28377-3_32</a>

Result language
angličtina
Original language name
Detection and modeling of alcohol intoxication dynamic from IR images based on clustering driven by ABC algorithm
Original language description
Alcohol detection is a challenging issue due to many aspects, especially to security reasons. Conventional measuring systems usually utilize a direct contact with the human body to obtain on spot alcohol level estimation. Nevertheless, it is well known that there are several side effects including the facial temperature distribution for alcohol detection. Since the facial temperature map is observable from the infrared (IR) records, we have performed a set of experimental measurements allowing for dynamical tracking of time-dependent effect of the alcohol intoxication. In this paper, we have proposed the clustering multiregional segmentation driven by the genetic optimization, particularly the Artificial Bee Colony (ABC) algorithm for the facial IR segmentation. The genetic optimization determines an optimal distribution of the initial cluster's centroids, which represent the main part of a proper clustering. Based on the segmentation procedure, we have proposed a dynamical model allowing for prediction of time-dependent alcohol intoxication features. (C) Springer Nature Switzerland AG 2019.
Czech name
—
Czech description
—

Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

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)

Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Volume 11683
ISBN
978-3-030-28376-6
ISSN
0302-9743
e-ISSN
1611-3349
Number of pages
10
Pages from-to
393-402
Publisher name
Springer
Place of publication
Cham
Event location
Hendaye
Event date
Sep 4, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
—

Similar results(10)