Locating intersections for autonomous vehicles: A Bayesian network approach

Kyoung Ho Choi; Sungkwan Joo; Seong Ik Cho; Jong Hyun Park

doi:10.4218/etrij.07.0206.0178

Locating intersections for autonomous vehicles: A Bayesian network approach

Kyoung Ho Choi, Sungkwan Joo, Seong Ik Cho, Jong Hyun Park

School of Electrical Engineering

Research output: Contribution to journal › Article › peer-review

9 Citations (Scopus)

Abstract

A novel idea is presented to locate intersections in a video sequence captured from a moving vehicle. More specifically, we propose a Bayesian network approach to combine evidence extracted from a video sequence and evidence from a database, maximizing evidence from various sensors in a systematic manner and locating intersections robustly.

Original language	English
Pages (from-to)	249-251
Number of pages	3
Journal	ETRI Journal
Volume	29
Issue number	2
DOIs	https://doi.org/10.4218/etrij.07.0206.0178
Publication status	Published - 2007 Apr

Keywords

Bayesian network
ITS
Navigation
Telematics

ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Computer Science(all)
Electrical and Electronic Engineering

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10.4218/etrij.07.0206.0178

Cite this

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title = "Locating intersections for autonomous vehicles: A Bayesian network approach",

abstract = "A novel idea is presented to locate intersections in a video sequence captured from a moving vehicle. More specifically, we propose a Bayesian network approach to combine evidence extracted from a video sequence and evidence from a database, maximizing evidence from various sensors in a systematic manner and locating intersections robustly.",

keywords = "Bayesian network, ITS, Navigation, Telematics",

author = "Choi, {Kyoung Ho} and Sungkwan Joo and Cho, {Seong Ik} and Park, {Jong Hyun}",

year = "2007",

month = apr,

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language = "English",

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T2 - A Bayesian network approach

AU - Choi, Kyoung Ho

AU - Joo, Sungkwan

AU - Cho, Seong Ik

AU - Park, Jong Hyun

PY - 2007/4

Y1 - 2007/4

N2 - A novel idea is presented to locate intersections in a video sequence captured from a moving vehicle. More specifically, we propose a Bayesian network approach to combine evidence extracted from a video sequence and evidence from a database, maximizing evidence from various sensors in a systematic manner and locating intersections robustly.

AB - A novel idea is presented to locate intersections in a video sequence captured from a moving vehicle. More specifically, we propose a Bayesian network approach to combine evidence extracted from a video sequence and evidence from a database, maximizing evidence from various sensors in a systematic manner and locating intersections robustly.

KW - Bayesian network

KW - ITS

KW - Navigation

KW - Telematics

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U2 - 10.4218/etrij.07.0206.0178

DO - 10.4218/etrij.07.0206.0178

M3 - Article

AN - SCOPUS:34147172731

SN - 1225-6463

VL - 29

SP - 249

EP - 251

JO - ETRI Journal

JF - ETRI Journal

IS - 2

ER -

Locating intersections for autonomous vehicles: A Bayesian network approach

Abstract

Keywords

ASJC Scopus subject areas

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