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Action  and  intention  recognition  of  pedestrians  in  urban  traffic
Halmstad University, Sweden.
Halmstad University, Sweden.
RISE - Research Institutes of Sweden, ICT, Viktoria.
RISE - Research Institutes of Sweden, ICT, Viktoria. Halmstad University, Sweden.ORCID iD: 0000-0002-1043-8773
2018 (English)Conference paper, Published paper (Other academic)
Abstract [en]

Action and intention recognition of pedestrians inurban  settings  are  challenging  problems  for  Advanced  DriverAssistance Systems as well as future autonomous vehicles tomaintain  smooth  and  safe  traffic.  This  work  investigates  anumber  of  feature  extraction  methods  in  combination  withseveral machine learning algorithms to build knowledge on howto automatically detect the action and intention of pedestriansin urban traffic. We focus on the motion and head orientationto predict whether the pedestrian is about to cross the street ornot. The work is based on the Joint Attention for AutonomousDriving   (JAAD)   dataset,   which   contains   346   videoclips   ofvarious traffic scenarios captured with cameras mounted in thewindshield  of  a  car.  An  accuracy  of  72%  for  head  orientationestimation  and  85%  for  motion  detection  is  obtained  in  our experiments.

Place, publisher, year, edition, pages
2018.
National Category
Natural Sciences
Identifiers
URN: urn:nbn:se:ri:diva-37631OAI: oai:DiVA.org:ri-37631DiVA, id: diva2:1283344
Conference
Intl Conf on Signal Image Technology & Internet Based Systems, SITIS 2018
Available from: 2019-01-29 Created: 2019-01-29 Last updated: 2019-01-29Bibliographically approved

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Englund, Cristofer

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
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Language
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  • en-GB
  • en-US
  • fi-FI
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  • Other locale
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Output format
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  • text
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  • rtf
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