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3D road curb extraction from image sequence for automobile parking assist system
We extract 3D curb from video sequence, using a single camera equipped with fish-eye lens and located at the front/rear of the vehicle. The challenge in extracting curbs from images lies in their small size and their lack of texture. We show that by appropriately exploiting appearance features, 3D g...
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creator | Prinet, Veronique JinSong Wang JongHo Lee Wettergreen, David |
description | We extract 3D curb from video sequence, using a single camera equipped with fish-eye lens and located at the front/rear of the vehicle. The challenge in extracting curbs from images lies in their small size and their lack of texture. We show that by appropriately exploiting appearance features, 3D geometry, and temporal information, one can reliably detect and localize the curbs in the 3D scene. The main underlying assumption of our model is that the road surface is flat and that the curb is approximately orthogonal to the road plane. We collected nine videos with ground truth, under day-time sunny weather condition, up to 2m range. Our experimental results compare favorably wrt the current the state-of-the-art on our database -90% precision rate in average and over 85% accuracy in curb height estimation. |
doi_str_mv | 10.1109/ICIP.2016.7533080 |
format | conference_proceeding |
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The challenge in extracting curbs from images lies in their small size and their lack of texture. We show that by appropriately exploiting appearance features, 3D geometry, and temporal information, one can reliably detect and localize the curbs in the 3D scene. The main underlying assumption of our model is that the road surface is flat and that the curb is approximately orthogonal to the road plane. We collected nine videos with ground truth, under day-time sunny weather condition, up to 2m range. Our experimental results compare favorably wrt the current the state-of-the-art on our database -90% precision rate in average and over 85% accuracy in curb height estimation.</description><identifier>EISSN: 2381-8549</identifier><identifier>EISBN: 9781467399616</identifier><identifier>EISBN: 1467399612</identifier><identifier>DOI: 10.1109/ICIP.2016.7533080</identifier><language>eng</language><publisher>IEEE</publisher><subject>Advanced Driving Assist Systems ; Cameras ; Computer Vision ; Feature extraction ; Image edge detection ; Roads ; Support vector machines ; Three-dimensional displays ; Vehicles ; Video Processing</subject><ispartof>2016 IEEE International Conference on Image Processing (ICIP), 2016, p.3847-3851</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/7533080$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,776,780,785,786,27904,54533,54910</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/7533080$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Prinet, Veronique</creatorcontrib><creatorcontrib>JinSong Wang</creatorcontrib><creatorcontrib>JongHo Lee</creatorcontrib><creatorcontrib>Wettergreen, David</creatorcontrib><title>3D road curb extraction from image sequence for automobile parking assist system</title><title>2016 IEEE International Conference on Image Processing (ICIP)</title><addtitle>ICIP</addtitle><description>We extract 3D curb from video sequence, using a single camera equipped with fish-eye lens and located at the front/rear of the vehicle. The challenge in extracting curbs from images lies in their small size and their lack of texture. We show that by appropriately exploiting appearance features, 3D geometry, and temporal information, one can reliably detect and localize the curbs in the 3D scene. The main underlying assumption of our model is that the road surface is flat and that the curb is approximately orthogonal to the road plane. We collected nine videos with ground truth, under day-time sunny weather condition, up to 2m range. Our experimental results compare favorably wrt the current the state-of-the-art on our database -90% precision rate in average and over 85% accuracy in curb height estimation.</description><subject>Advanced Driving Assist Systems</subject><subject>Cameras</subject><subject>Computer Vision</subject><subject>Feature extraction</subject><subject>Image edge detection</subject><subject>Roads</subject><subject>Support vector machines</subject><subject>Three-dimensional displays</subject><subject>Vehicles</subject><subject>Video Processing</subject><issn>2381-8549</issn><isbn>9781467399616</isbn><isbn>1467399612</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2016</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNotkM1KAzEURqMgWGsfQNzkBWbMzc9kspRR60DBLnRdMjM3JdppapIB-_ZW7OpsDoePj5A7YCUAMw9t065LzqAqtRKC1eyCLIyuQVZaGFNBdUlmXNRQ1Eqaa3KT0idjJ1_AjKzFE43BDrSfYkfxJ0fbZx_21MUwUj_aLdKE3xPue6QuRGqnHMbQ-R3Sg41ffr-lNiWfMk3HlHG8JVfO7hIuzpyTj5fn9-a1WL0t2-ZxVXjQKhdgXY1DVWMHqISTwg0IUiLvmNGyHzrmALnRqvuTLDPYK6eEVJwDc-jEnNz_dz0ibg7xNDUeN-cDxC-7mVBa</recordid><startdate>201609</startdate><enddate>201609</enddate><creator>Prinet, Veronique</creator><creator>JinSong Wang</creator><creator>JongHo Lee</creator><creator>Wettergreen, David</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope></search><sort><creationdate>201609</creationdate><title>3D road curb extraction from image sequence for automobile parking assist system</title><author>Prinet, Veronique ; JinSong Wang ; JongHo Lee ; Wettergreen, David</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-1af8ed68eb1e53f43fde144e2b0974cdb0f1e2975bd68ea09ec5f53452210fef3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Advanced Driving Assist Systems</topic><topic>Cameras</topic><topic>Computer Vision</topic><topic>Feature extraction</topic><topic>Image edge detection</topic><topic>Roads</topic><topic>Support vector machines</topic><topic>Three-dimensional displays</topic><topic>Vehicles</topic><topic>Video Processing</topic><toplevel>online_resources</toplevel><creatorcontrib>Prinet, Veronique</creatorcontrib><creatorcontrib>JinSong Wang</creatorcontrib><creatorcontrib>JongHo Lee</creatorcontrib><creatorcontrib>Wettergreen, David</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Prinet, Veronique</au><au>JinSong Wang</au><au>JongHo Lee</au><au>Wettergreen, David</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>3D road curb extraction from image sequence for automobile parking assist system</atitle><btitle>2016 IEEE International Conference on Image Processing (ICIP)</btitle><stitle>ICIP</stitle><date>2016-09</date><risdate>2016</risdate><spage>3847</spage><epage>3851</epage><pages>3847-3851</pages><eissn>2381-8549</eissn><eisbn>9781467399616</eisbn><eisbn>1467399612</eisbn><abstract>We extract 3D curb from video sequence, using a single camera equipped with fish-eye lens and located at the front/rear of the vehicle. The challenge in extracting curbs from images lies in their small size and their lack of texture. We show that by appropriately exploiting appearance features, 3D geometry, and temporal information, one can reliably detect and localize the curbs in the 3D scene. The main underlying assumption of our model is that the road surface is flat and that the curb is approximately orthogonal to the road plane. We collected nine videos with ground truth, under day-time sunny weather condition, up to 2m range. Our experimental results compare favorably wrt the current the state-of-the-art on our database -90% precision rate in average and over 85% accuracy in curb height estimation.</abstract><pub>IEEE</pub><doi>10.1109/ICIP.2016.7533080</doi><tpages>5</tpages></addata></record> |
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identifier | EISSN: 2381-8549 |
ispartof | 2016 IEEE International Conference on Image Processing (ICIP), 2016, p.3847-3851 |
issn | 2381-8549 |
language | eng |
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source | IEEE Xplore All Conference Series |
subjects | Advanced Driving Assist Systems Cameras Computer Vision Feature extraction Image edge detection Roads Support vector machines Three-dimensional displays Vehicles Video Processing |
title | 3D road curb extraction from image sequence for automobile parking assist system |
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