Estimating pedestrian intentions from trajectory data
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F19%3A10404227" target="_blank" >RIV/00216208:11320/19:10404227 - isvavai.cz</a>
Alternative codes found
RIV/68407700:21730/19:00340402
Result on the web
<a href="https://doi.org/10.1109/ICCP48234.2019.8959707" target="_blank" >https://doi.org/10.1109/ICCP48234.2019.8959707</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ICCP48234.2019.8959707" target="_blank" >10.1109/ICCP48234.2019.8959707</a>
Alternative languages
Result language
angličtina
Original language name
Estimating pedestrian intentions from trajectory data
Original language description
In this paper, several machine learning methods are used to train classifiers capable of estimating the intention of a pedestrian to cross a zebra crossing. Their results are compared to a Bayesian network-an approach commonly used in autonomous driving. The data used for the estimation contain only position and heading of the pedestrians.
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
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2019 IEEE 15th International Conference on Intelligent Computer Communication and Processing (ICCP)
ISBN
978-1-72814-914-1
ISSN
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e-ISSN
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Number of pages
7
Pages from-to
19-25
Publisher name
IEEE
Place of publication
Cluj-Napoca, Romania
Event location
Cluj-Napoca, Romania
Event date
Sep 5, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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