Robust vision based lane tracking using multiple cues and particle filtering

One of the more startling effects of road related accidents is the economic and social burden they cause. Between 750,000 and 880,000 people died globally in road related accidents in 1999 alone, with an estimated cost of US518 billion. One way of combating this problem is to develop Intelligent Veh...

Full description

Saved in:
Bibliographic Details
Main Authors: Apostoloff, N., Zelinsky, A.
Format: Conference Proceeding
Language:English
Subjects:
Australia
Cameras
Fatigue
Filtering
Intelligent vehicles
Particle tracking
Remotely operated vehicles
Road vehicles
Robustness
Vehicle driving
Citations: Items that cite this one
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c288t-e1211323cac84ff1484b3945a36c8376ec7ab6e6e3bc06634b08e244aba8899c3
cites
container_end_page 563
container_issue
container_start_page 558
container_title
container_volume
creator Apostoloff, N.
Zelinsky, A.
description One of the more startling effects of road related accidents is the economic and social burden they cause. Between 750,000 and 880,000 people died globally in road related accidents in 1999 alone, with an estimated cost of US518 billion. One way of combating this problem is to develop Intelligent Vehicles that are self-aware and act to increase the safety of the transportation system. This paper presents the development and application of a novel multiple-cue visual lane tracking system for research into Intelligent Vehicles (IV). Particle filtering and cue fusion technologies form the basis of the lane tracking system which robustly handles several of the problems faced by previous lane tracking systems such as shadows on the road, unreliable lane markings, dramatic lighting changes and discontinuous changes in road characteristics and types. Experimental results of the lane tracking system running at 15 Hz will be discussed, focusing on the particle filter and cue fusion technology used.
doi_str_mv 10.1109/IVS.2003.1212973
format conference_proceeding
fullrecord <record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_1212973</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>1212973</ieee_id><sourcerecordid>1212973</sourcerecordid><originalsourceid>FETCH-LOGICAL-c288t-e1211323cac84ff1484b3945a36c8376ec7ab6e6e3bc06634b08e244aba8899c3</originalsourceid><addsrcrecordid>eNotT8tqwzAQFJRCS-p7oRf9gF1Jq-hxLKGPQKDQ1zWslHVR6zjGkgv9-7okwzADw7LMMHYtRSOl8Lfrj9dGCQGNVFJ5C2es8taJmWCddnDBqpy_xAy91EbbS7Z5OYQpF_6Tcjr0PGCmHe-wJ15GjN-p_-RT_tf91JU0dMTjRJljv-MDjiXFOWlTV2icj67YeYtdpurkC_b-cP-2eqo3z4_r1d2mjsq5UtPcToKCiNHptpXa6QBeLxFMdGANRYvBkCEIURgDOghHSmsM6Jz3ERbs5vg3EdF2GNMex9_taTP8AZh3TKs</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>Robust vision based lane tracking using multiple cues and particle filtering</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Apostoloff, N. ; Zelinsky, A.</creator><creatorcontrib>Apostoloff, N. ; Zelinsky, A.</creatorcontrib><description>One of the more startling effects of road related accidents is the economic and social burden they cause. Between 750,000 and 880,000 people died globally in road related accidents in 1999 alone, with an estimated cost of US518 billion. One way of combating this problem is to develop Intelligent Vehicles that are self-aware and act to increase the safety of the transportation system. This paper presents the development and application of a novel multiple-cue visual lane tracking system for research into Intelligent Vehicles (IV). Particle filtering and cue fusion technologies form the basis of the lane tracking system which robustly handles several of the problems faced by previous lane tracking systems such as shadows on the road, unreliable lane markings, dramatic lighting changes and discontinuous changes in road characteristics and types. Experimental results of the lane tracking system running at 15 Hz will be discussed, focusing on the particle filter and cue fusion technology used.</description><identifier>ISBN: 9780780378483</identifier><identifier>ISBN: 0780378482</identifier><identifier>DOI: 10.1109/IVS.2003.1212973</identifier><language>eng</language><publisher>IEEE</publisher><subject>Australia ; Cameras ; Fatigue ; Filtering ; Intelligent vehicles ; Particle tracking ; Remotely operated vehicles ; Road vehicles ; Robustness ; Vehicle driving</subject><ispartof>IEEE IV2003 Intelligent Vehicles Symposium. Proceedings (Cat. No.03TH8683), 2003, p.558-563</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c288t-e1211323cac84ff1484b3945a36c8376ec7ab6e6e3bc06634b08e244aba8899c3</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/1212973$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,776,780,785,786,2051,4035,4036,27904,54898</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/1212973$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Apostoloff, N.</creatorcontrib><creatorcontrib>Zelinsky, A.</creatorcontrib><title>Robust vision based lane tracking using multiple cues and particle filtering</title><title>IEEE IV2003 Intelligent Vehicles Symposium. Proceedings (Cat. No.03TH8683)</title><addtitle>IVS</addtitle><description>One of the more startling effects of road related accidents is the economic and social burden they cause. Between 750,000 and 880,000 people died globally in road related accidents in 1999 alone, with an estimated cost of US518 billion. One way of combating this problem is to develop Intelligent Vehicles that are self-aware and act to increase the safety of the transportation system. This paper presents the development and application of a novel multiple-cue visual lane tracking system for research into Intelligent Vehicles (IV). Particle filtering and cue fusion technologies form the basis of the lane tracking system which robustly handles several of the problems faced by previous lane tracking systems such as shadows on the road, unreliable lane markings, dramatic lighting changes and discontinuous changes in road characteristics and types. Experimental results of the lane tracking system running at 15 Hz will be discussed, focusing on the particle filter and cue fusion technology used.</description><subject>Australia</subject><subject>Cameras</subject><subject>Fatigue</subject><subject>Filtering</subject><subject>Intelligent vehicles</subject><subject>Particle tracking</subject><subject>Remotely operated vehicles</subject><subject>Road vehicles</subject><subject>Robustness</subject><subject>Vehicle driving</subject><isbn>9780780378483</isbn><isbn>0780378482</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2003</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNotT8tqwzAQFJRCS-p7oRf9gF1Jq-hxLKGPQKDQ1zWslHVR6zjGkgv9-7okwzADw7LMMHYtRSOl8Lfrj9dGCQGNVFJ5C2es8taJmWCddnDBqpy_xAy91EbbS7Z5OYQpF_6Tcjr0PGCmHe-wJ15GjN-p_-RT_tf91JU0dMTjRJljv-MDjiXFOWlTV2icj67YeYtdpurkC_b-cP-2eqo3z4_r1d2mjsq5UtPcToKCiNHptpXa6QBeLxFMdGANRYvBkCEIURgDOghHSmsM6Jz3ERbs5vg3EdF2GNMex9_taTP8AZh3TKs</recordid><startdate>2003</startdate><enddate>2003</enddate><creator>Apostoloff, N.</creator><creator>Zelinsky, A.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>2003</creationdate><title>Robust vision based lane tracking using multiple cues and particle filtering</title><author>Apostoloff, N. ; Zelinsky, A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c288t-e1211323cac84ff1484b3945a36c8376ec7ab6e6e3bc06634b08e244aba8899c3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2003</creationdate><topic>Australia</topic><topic>Cameras</topic><topic>Fatigue</topic><topic>Filtering</topic><topic>Intelligent vehicles</topic><topic>Particle tracking</topic><topic>Remotely operated vehicles</topic><topic>Road vehicles</topic><topic>Robustness</topic><topic>Vehicle driving</topic><toplevel>online_resources</toplevel><creatorcontrib>Apostoloff, N.</creatorcontrib><creatorcontrib>Zelinsky, A.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Apostoloff, N.</au><au>Zelinsky, A.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Robust vision based lane tracking using multiple cues and particle filtering</atitle><btitle>IEEE IV2003 Intelligent Vehicles Symposium. Proceedings (Cat. No.03TH8683)</btitle><stitle>IVS</stitle><date>2003</date><risdate>2003</risdate><spage>558</spage><epage>563</epage><pages>558-563</pages><isbn>9780780378483</isbn><isbn>0780378482</isbn><abstract>One of the more startling effects of road related accidents is the economic and social burden they cause. Between 750,000 and 880,000 people died globally in road related accidents in 1999 alone, with an estimated cost of US518 billion. One way of combating this problem is to develop Intelligent Vehicles that are self-aware and act to increase the safety of the transportation system. This paper presents the development and application of a novel multiple-cue visual lane tracking system for research into Intelligent Vehicles (IV). Particle filtering and cue fusion technologies form the basis of the lane tracking system which robustly handles several of the problems faced by previous lane tracking systems such as shadows on the road, unreliable lane markings, dramatic lighting changes and discontinuous changes in road characteristics and types. Experimental results of the lane tracking system running at 15 Hz will be discussed, focusing on the particle filter and cue fusion technology used.</abstract><pub>IEEE</pub><doi>10.1109/IVS.2003.1212973</doi><tpages>6</tpages></addata></record>
fulltext fulltext_linktorsrc
identifier ISBN: 9780780378483
ispartof IEEE IV2003 Intelligent Vehicles Symposium. Proceedings (Cat. No.03TH8683), 2003, p.558-563
issn
language eng
recordid cdi_ieee_primary_1212973
source IEEE Electronic Library (IEL) Conference Proceedings
subjects Australia
Cameras
Fatigue
Filtering
Intelligent vehicles
Particle tracking
Remotely operated vehicles
Road vehicles
Robustness
Vehicle driving
title Robust vision based lane tracking using multiple cues and particle filtering
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-25T18%3A08%3A17IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Robust%20vision%20based%20lane%20tracking%20using%20multiple%20cues%20and%20particle%20filtering&rft.btitle=IEEE%20IV2003%20Intelligent%20Vehicles%20Symposium.%20Proceedings%20(Cat.%20No.03TH8683)&rft.au=Apostoloff,%20N.&rft.date=2003&rft.spage=558&rft.epage=563&rft.pages=558-563&rft.isbn=9780780378483&rft.isbn_list=0780378482&rft_id=info:doi/10.1109/IVS.2003.1212973&rft_dat=%3Cieee_6IE%3E1212973%3C/ieee_6IE%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c288t-e1211323cac84ff1484b3945a36c8376ec7ab6e6e3bc06634b08e244aba8899c3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=1212973&rfr_iscdi=true