Loading…

Improvement of feature matching in catadioptric images using gyroscope data

Most of vision-based algorithms for motion and localization estimation requires matching some interest points in a pair of images. After building feature correspondence, it is possible to estimate camera motion/localization using epipolar geometry. However feature matching is still a challenging pro...

Full description

Saved in:
Bibliographic Details
Main Authors: Bazin, J.-C., Inso Kweon, Demonceaux, C., Vasseur, P.
Format: Conference Proceeding
Language:English
Subjects:
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by
cites
container_end_page 5
container_issue
container_start_page 1
container_title
container_volume
creator Bazin, J.-C.
Inso Kweon
Demonceaux, C.
Vasseur, P.
description Most of vision-based algorithms for motion and localization estimation requires matching some interest points in a pair of images. After building feature correspondence, it is possible to estimate camera motion/localization using epipolar geometry. However feature matching is still a challenging problem because of time constraint or image variability for example. In several robotic applications, the camera rotation may be known thanks to a gyroscope or another orientation sensor. Therefore, in this paper, we aim to answer the following question: can the knowledge of rotation from a gyroscope be used to improve feature matching. To analyze this new approach of camera and gyroscope data fusion, we proceed in two steps. First, we rotationally align the images using rotation information of the gyroscope. And second, we compare the quality of feature matching in the original and rotationally aligned images. Experimental results on a real catadioptric sequence show that gyroscope data permits to sensibly improve the number of inliers according to epipolar geometry.
doi_str_mv 10.1109/ICPR.2008.4761039
format conference_proceeding
fullrecord <record><control><sourceid>ieee_CHZPO</sourceid><recordid>TN_cdi_ieee_primary_4761039</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>4761039</ieee_id><sourcerecordid>4761039</sourcerecordid><originalsourceid>FETCH-LOGICAL-i90t-9c6297b5eeab88931369b501516b702c617c0e1ea21840b9f64f6efcf1b3d67f3</originalsourceid><addsrcrecordid>eNpVkEtLw0AUhccXWGt_gLiZP5B677xnKcVHsaBI92UyuRNHTBOSVOi_t2I3rs7iO3wcDmM3CHNE8HfLxdv7XAC4ubIGQfoTNvPWoRJKCbTanLKJcBILq6w--8eUP2cTBI2FMhov2dUwfAIIkNpN2Muy6fr2mxrajrxNPFEYdz3xJozxI29rnrc8hjFUue3GPkeem1DTwHfDL6z3fTvEtiNeHTrX7CKFr4Fmx5yy9ePDevFcrF6flov7VZE9jIWPRnhbaqJQOuclSuNLDajRlBZENGgjEFIQ6BSUPhmVDKWYsJSVsUlO2e2fNhPRpusPi_r95niL_AELiVJW</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>Improvement of feature matching in catadioptric images using gyroscope data</title><source>IEEE Xplore All Conference Series</source><creator>Bazin, J.-C. ; Inso Kweon ; Demonceaux, C. ; Vasseur, P.</creator><creatorcontrib>Bazin, J.-C. ; Inso Kweon ; Demonceaux, C. ; Vasseur, P.</creatorcontrib><description>Most of vision-based algorithms for motion and localization estimation requires matching some interest points in a pair of images. After building feature correspondence, it is possible to estimate camera motion/localization using epipolar geometry. However feature matching is still a challenging problem because of time constraint or image variability for example. In several robotic applications, the camera rotation may be known thanks to a gyroscope or another orientation sensor. Therefore, in this paper, we aim to answer the following question: can the knowledge of rotation from a gyroscope be used to improve feature matching. To analyze this new approach of camera and gyroscope data fusion, we proceed in two steps. First, we rotationally align the images using rotation information of the gyroscope. And second, we compare the quality of feature matching in the original and rotationally aligned images. Experimental results on a real catadioptric sequence show that gyroscope data permits to sensibly improve the number of inliers according to epipolar geometry.</description><identifier>ISSN: 1051-4651</identifier><identifier>ISBN: 9781424421749</identifier><identifier>ISBN: 1424421748</identifier><identifier>EISSN: 2831-7475</identifier><identifier>EISBN: 9781424421756</identifier><identifier>EISBN: 1424421756</identifier><identifier>DOI: 10.1109/ICPR.2008.4761039</identifier><language>eng</language><publisher>IEEE</publisher><subject>Cameras ; Feature extraction ; Geometry ; Gyroscopes ; Lighting ; Mirrors ; Motion estimation ; Noise robustness ; Robot sensing systems ; Robot vision systems</subject><ispartof>2008 19th International Conference on Pattern Recognition, 2008, p.1-5</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/4761039$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2058,27925,54555,54920,54932</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/4761039$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Bazin, J.-C.</creatorcontrib><creatorcontrib>Inso Kweon</creatorcontrib><creatorcontrib>Demonceaux, C.</creatorcontrib><creatorcontrib>Vasseur, P.</creatorcontrib><title>Improvement of feature matching in catadioptric images using gyroscope data</title><title>2008 19th International Conference on Pattern Recognition</title><addtitle>ICPR</addtitle><description>Most of vision-based algorithms for motion and localization estimation requires matching some interest points in a pair of images. After building feature correspondence, it is possible to estimate camera motion/localization using epipolar geometry. However feature matching is still a challenging problem because of time constraint or image variability for example. In several robotic applications, the camera rotation may be known thanks to a gyroscope or another orientation sensor. Therefore, in this paper, we aim to answer the following question: can the knowledge of rotation from a gyroscope be used to improve feature matching. To analyze this new approach of camera and gyroscope data fusion, we proceed in two steps. First, we rotationally align the images using rotation information of the gyroscope. And second, we compare the quality of feature matching in the original and rotationally aligned images. Experimental results on a real catadioptric sequence show that gyroscope data permits to sensibly improve the number of inliers according to epipolar geometry.</description><subject>Cameras</subject><subject>Feature extraction</subject><subject>Geometry</subject><subject>Gyroscopes</subject><subject>Lighting</subject><subject>Mirrors</subject><subject>Motion estimation</subject><subject>Noise robustness</subject><subject>Robot sensing systems</subject><subject>Robot vision systems</subject><issn>1051-4651</issn><issn>2831-7475</issn><isbn>9781424421749</isbn><isbn>1424421748</isbn><isbn>9781424421756</isbn><isbn>1424421756</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2008</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNpVkEtLw0AUhccXWGt_gLiZP5B677xnKcVHsaBI92UyuRNHTBOSVOi_t2I3rs7iO3wcDmM3CHNE8HfLxdv7XAC4ubIGQfoTNvPWoRJKCbTanLKJcBILq6w--8eUP2cTBI2FMhov2dUwfAIIkNpN2Muy6fr2mxrajrxNPFEYdz3xJozxI29rnrc8hjFUue3GPkeem1DTwHfDL6z3fTvEtiNeHTrX7CKFr4Fmx5yy9ePDevFcrF6flov7VZE9jIWPRnhbaqJQOuclSuNLDajRlBZENGgjEFIQ6BSUPhmVDKWYsJSVsUlO2e2fNhPRpusPi_r95niL_AELiVJW</recordid><startdate>200812</startdate><enddate>200812</enddate><creator>Bazin, J.-C.</creator><creator>Inso Kweon</creator><creator>Demonceaux, C.</creator><creator>Vasseur, P.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>200812</creationdate><title>Improvement of feature matching in catadioptric images using gyroscope data</title><author>Bazin, J.-C. ; Inso Kweon ; Demonceaux, C. ; Vasseur, P.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-9c6297b5eeab88931369b501516b702c617c0e1ea21840b9f64f6efcf1b3d67f3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2008</creationdate><topic>Cameras</topic><topic>Feature extraction</topic><topic>Geometry</topic><topic>Gyroscopes</topic><topic>Lighting</topic><topic>Mirrors</topic><topic>Motion estimation</topic><topic>Noise robustness</topic><topic>Robot sensing systems</topic><topic>Robot vision systems</topic><toplevel>online_resources</toplevel><creatorcontrib>Bazin, J.-C.</creatorcontrib><creatorcontrib>Inso Kweon</creatorcontrib><creatorcontrib>Demonceaux, C.</creatorcontrib><creatorcontrib>Vasseur, P.</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 Online</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>Bazin, J.-C.</au><au>Inso Kweon</au><au>Demonceaux, C.</au><au>Vasseur, P.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Improvement of feature matching in catadioptric images using gyroscope data</atitle><btitle>2008 19th International Conference on Pattern Recognition</btitle><stitle>ICPR</stitle><date>2008-12</date><risdate>2008</risdate><spage>1</spage><epage>5</epage><pages>1-5</pages><issn>1051-4651</issn><eissn>2831-7475</eissn><isbn>9781424421749</isbn><isbn>1424421748</isbn><eisbn>9781424421756</eisbn><eisbn>1424421756</eisbn><abstract>Most of vision-based algorithms for motion and localization estimation requires matching some interest points in a pair of images. After building feature correspondence, it is possible to estimate camera motion/localization using epipolar geometry. However feature matching is still a challenging problem because of time constraint or image variability for example. In several robotic applications, the camera rotation may be known thanks to a gyroscope or another orientation sensor. Therefore, in this paper, we aim to answer the following question: can the knowledge of rotation from a gyroscope be used to improve feature matching. To analyze this new approach of camera and gyroscope data fusion, we proceed in two steps. First, we rotationally align the images using rotation information of the gyroscope. And second, we compare the quality of feature matching in the original and rotationally aligned images. Experimental results on a real catadioptric sequence show that gyroscope data permits to sensibly improve the number of inliers according to epipolar geometry.</abstract><pub>IEEE</pub><doi>10.1109/ICPR.2008.4761039</doi><tpages>5</tpages></addata></record>
fulltext fulltext_linktorsrc
identifier ISSN: 1051-4651
ispartof 2008 19th International Conference on Pattern Recognition, 2008, p.1-5
issn 1051-4651
2831-7475
language eng
recordid cdi_ieee_primary_4761039
source IEEE Xplore All Conference Series
subjects Cameras
Feature extraction
Geometry
Gyroscopes
Lighting
Mirrors
Motion estimation
Noise robustness
Robot sensing systems
Robot vision systems
title Improvement of feature matching in catadioptric images using gyroscope data
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-24T09%3A05%3A33IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_CHZPO&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Improvement%20of%20feature%20matching%20in%20catadioptric%20images%20using%20gyroscope%20data&rft.btitle=2008%2019th%20International%20Conference%20on%20Pattern%20Recognition&rft.au=Bazin,%20J.-C.&rft.date=2008-12&rft.spage=1&rft.epage=5&rft.pages=1-5&rft.issn=1051-4651&rft.eissn=2831-7475&rft.isbn=9781424421749&rft.isbn_list=1424421748&rft_id=info:doi/10.1109/ICPR.2008.4761039&rft.eisbn=9781424421756&rft.eisbn_list=1424421756&rft_dat=%3Cieee_CHZPO%3E4761039%3C/ieee_CHZPO%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-i90t-9c6297b5eeab88931369b501516b702c617c0e1ea21840b9f64f6efcf1b3d67f3%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=4761039&rfr_iscdi=true