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Saliency map based analysis for prediction of car driving difficulty in Google street view scenes

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Citations (Scopus)

Abstract

The paper describes how the saliency maps - computational models of visual attention can be used to predict car driving difficulty. The peak number and areas are analyzed for the images are obtained from Google Street View. As a ground truth the crowd sourced average human responses on the speed and subjective driving difficulty are used.

Original languageEnglish
Title of host publicationInternational Conference of Numerical Analysis and Applied Mathematics, ICNAAM 2017
EditorsCharalambos Tsitouras, Theodore Simos, Theodore Simos, Theodore Simos, Theodore Simos, Theodore Simos
PublisherAmerican Institute of Physics Inc.
ISBN (Electronic)9780735416901
DOIs
Publication statusPublished - 10 Jul 2018
EventInternational Conference of Numerical Analysis and Applied Mathematics, ICNAAM 2017 - Thessaloniki, Greece
Duration: 25 Sept 201730 Sept 2017

Publication series

NameAIP Conference Proceedings
Volume1978
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

ConferenceInternational Conference of Numerical Analysis and Applied Mathematics, ICNAAM 2017
Country/TerritoryGreece
CityThessaloniki
Period25/09/1730/09/17

ASJC Scopus subject areas

  • General Physics and Astronomy

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