Active vector graph for regularized tesselation
A discretized parametric curve can be seen as a sparse graph of vectors where each vertex is linked to two other vertices. Following this observation, we propose to generalize parametric active contours to a larger framework we call active vector graphs. This can be achieved by allowing each vertex...
Gespeichert in:
1. Verfasser: | |
---|---|
Format: | Tagungsbericht |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext bestellen |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 2432 |
---|---|
container_issue | |
container_start_page | 2429 |
container_title | |
container_volume | |
creator | Genovesio, A. |
description | A discretized parametric curve can be seen as a sparse graph of vectors where each vertex is linked to two other vertices. Following this observation, we propose to generalize parametric active contours to a larger framework we call active vector graphs. This can be achieved by allowing each vertex of a graph of vectors to be linked to more than two vertices. An active graph does not need to be parameterized and the computation of its energy can be achieved by integrating over all its vertices. The optimization scheme pushes the graph toward the edges and in the direction of the normal which we show can be defined for all vertices. This offers a regularized model which addresses in an elegant and very fast way a certain set of problems such as the segmentation of connected regions. The method is described along with an example. |
doi_str_mv | 10.1109/ICIP.2009.5414154 |
format | Conference Proceeding |
fullrecord | <record><control><sourceid>hal_6IE</sourceid><recordid>TN_cdi_ieee_primary_5414154</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>5414154</ieee_id><sourcerecordid>oai_HAL_hal_02902022v1</sourcerecordid><originalsourceid>FETCH-LOGICAL-h209t-3a1d63b6f4da8b428f74b7176e9cd8abebd5f46bcc2f5cd0a0b56f9040d70a383</originalsourceid><addsrcrecordid>eNpVkE9Lw0AQxdd_YK39AOIlVw9pZ3ZnN7vHUNQGAnrQc9jN7raRaEoSC_rprbQInt5j3o8H8xi7QZgjglkUy-J5zgHMXBISSjphM5NpJE4klZRwyiZcaEy1JHP2LxPqnE1Qcp6S1nDJrobhDYADCpywRV6PzS4ku1CPXZ-se7vdJHHv-rD-bG3ffAefjGEYQmvHpvu4ZhfRtkOYHXXKXh_uX5artHx6LJZ5mW44mDEVFr0STkXyVjviOmbkMsxUMLXX1gXnZSTl6ppHWXuw4KSKBgh8BlZoMWV3h96Nbatt37zb_qvqbFOt8rL6vQE3-x843-GevT2wTQjhDz7uJH4Aaz5Whg</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>Active vector graph for regularized tesselation</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Genovesio, A.</creator><creatorcontrib>Genovesio, A.</creatorcontrib><description>A discretized parametric curve can be seen as a sparse graph of vectors where each vertex is linked to two other vertices. Following this observation, we propose to generalize parametric active contours to a larger framework we call active vector graphs. This can be achieved by allowing each vertex of a graph of vectors to be linked to more than two vertices. An active graph does not need to be parameterized and the computation of its energy can be achieved by integrating over all its vertices. The optimization scheme pushes the graph toward the edges and in the direction of the normal which we show can be defined for all vertices. This offers a regularized model which addresses in an elegant and very fast way a certain set of problems such as the segmentation of connected regions. The method is described along with an example.</description><identifier>ISSN: 1522-4880</identifier><identifier>ISBN: 9781424456536</identifier><identifier>ISBN: 1424456533</identifier><identifier>EISSN: 2381-8549</identifier><identifier>EISBN: 9781424456550</identifier><identifier>EISBN: 9781424456543</identifier><identifier>EISBN: 142445655X</identifier><identifier>EISBN: 1424456541</identifier><identifier>DOI: 10.1109/ICIP.2009.5414154</identifier><language>eng</language><publisher>IEEE</publisher><subject>active contour ; Active contours ; Computer Science ; Equations ; Graph ; Image edge detection ; Image segmentation ; Object detection ; Pixel ; Tesselation ; Trajectory</subject><ispartof>2009 16th IEEE International Conference on Image Processing (ICIP), 2009, p.2429-2432</ispartof><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><woscitedreferencessubscribed>false</woscitedreferencessubscribed><orcidid>0000-0003-1877-5595</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/5414154$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,885,2058,27925,54920</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/5414154$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc><backlink>$$Uhttps://hal.science/hal-02902022$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Genovesio, A.</creatorcontrib><title>Active vector graph for regularized tesselation</title><title>2009 16th IEEE International Conference on Image Processing (ICIP)</title><addtitle>ICIP</addtitle><description>A discretized parametric curve can be seen as a sparse graph of vectors where each vertex is linked to two other vertices. Following this observation, we propose to generalize parametric active contours to a larger framework we call active vector graphs. This can be achieved by allowing each vertex of a graph of vectors to be linked to more than two vertices. An active graph does not need to be parameterized and the computation of its energy can be achieved by integrating over all its vertices. The optimization scheme pushes the graph toward the edges and in the direction of the normal which we show can be defined for all vertices. This offers a regularized model which addresses in an elegant and very fast way a certain set of problems such as the segmentation of connected regions. The method is described along with an example.</description><subject>active contour</subject><subject>Active contours</subject><subject>Computer Science</subject><subject>Equations</subject><subject>Graph</subject><subject>Image edge detection</subject><subject>Image segmentation</subject><subject>Object detection</subject><subject>Pixel</subject><subject>Tesselation</subject><subject>Trajectory</subject><issn>1522-4880</issn><issn>2381-8549</issn><isbn>9781424456536</isbn><isbn>1424456533</isbn><isbn>9781424456550</isbn><isbn>9781424456543</isbn><isbn>142445655X</isbn><isbn>1424456541</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2009</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNpVkE9Lw0AQxdd_YK39AOIlVw9pZ3ZnN7vHUNQGAnrQc9jN7raRaEoSC_rprbQInt5j3o8H8xi7QZgjglkUy-J5zgHMXBISSjphM5NpJE4klZRwyiZcaEy1JHP2LxPqnE1Qcp6S1nDJrobhDYADCpywRV6PzS4ku1CPXZ-se7vdJHHv-rD-bG3ffAefjGEYQmvHpvu4ZhfRtkOYHXXKXh_uX5artHx6LJZ5mW44mDEVFr0STkXyVjviOmbkMsxUMLXX1gXnZSTl6ppHWXuw4KSKBgh8BlZoMWV3h96Nbatt37zb_qvqbFOt8rL6vQE3-x843-GevT2wTQjhDz7uJH4Aaz5Whg</recordid><startdate>200911</startdate><enddate>200911</enddate><creator>Genovesio, A.</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope><scope>1XC</scope><orcidid>https://orcid.org/0000-0003-1877-5595</orcidid></search><sort><creationdate>200911</creationdate><title>Active vector graph for regularized tesselation</title><author>Genovesio, A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-h209t-3a1d63b6f4da8b428f74b7176e9cd8abebd5f46bcc2f5cd0a0b56f9040d70a383</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2009</creationdate><topic>active contour</topic><topic>Active contours</topic><topic>Computer Science</topic><topic>Equations</topic><topic>Graph</topic><topic>Image edge detection</topic><topic>Image segmentation</topic><topic>Object detection</topic><topic>Pixel</topic><topic>Tesselation</topic><topic>Trajectory</topic><toplevel>online_resources</toplevel><creatorcontrib>Genovesio, A.</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><collection>Hyper Article en Ligne (HAL)</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Genovesio, A.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Active vector graph for regularized tesselation</atitle><btitle>2009 16th IEEE International Conference on Image Processing (ICIP)</btitle><stitle>ICIP</stitle><date>2009-11</date><risdate>2009</risdate><spage>2429</spage><epage>2432</epage><pages>2429-2432</pages><issn>1522-4880</issn><eissn>2381-8549</eissn><isbn>9781424456536</isbn><isbn>1424456533</isbn><eisbn>9781424456550</eisbn><eisbn>9781424456543</eisbn><eisbn>142445655X</eisbn><eisbn>1424456541</eisbn><abstract>A discretized parametric curve can be seen as a sparse graph of vectors where each vertex is linked to two other vertices. Following this observation, we propose to generalize parametric active contours to a larger framework we call active vector graphs. This can be achieved by allowing each vertex of a graph of vectors to be linked to more than two vertices. An active graph does not need to be parameterized and the computation of its energy can be achieved by integrating over all its vertices. The optimization scheme pushes the graph toward the edges and in the direction of the normal which we show can be defined for all vertices. This offers a regularized model which addresses in an elegant and very fast way a certain set of problems such as the segmentation of connected regions. The method is described along with an example.</abstract><pub>IEEE</pub><doi>10.1109/ICIP.2009.5414154</doi><tpages>4</tpages><orcidid>https://orcid.org/0000-0003-1877-5595</orcidid></addata></record> |
fulltext | fulltext_linktorsrc |
identifier | ISSN: 1522-4880 |
ispartof | 2009 16th IEEE International Conference on Image Processing (ICIP), 2009, p.2429-2432 |
issn | 1522-4880 2381-8549 |
language | eng |
recordid | cdi_ieee_primary_5414154 |
source | IEEE Electronic Library (IEL) Conference Proceedings |
subjects | active contour Active contours Computer Science Equations Graph Image edge detection Image segmentation Object detection Pixel Tesselation Trajectory |
title | Active vector graph for regularized tesselation |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-23T03%3A47%3A15IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-hal_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Active%20vector%20graph%20for%20regularized%20tesselation&rft.btitle=2009%2016th%20IEEE%20International%20Conference%20on%20Image%20Processing%20(ICIP)&rft.au=Genovesio,%20A.&rft.date=2009-11&rft.spage=2429&rft.epage=2432&rft.pages=2429-2432&rft.issn=1522-4880&rft.eissn=2381-8549&rft.isbn=9781424456536&rft.isbn_list=1424456533&rft_id=info:doi/10.1109/ICIP.2009.5414154&rft_dat=%3Chal_6IE%3Eoai_HAL_hal_02902022v1%3C/hal_6IE%3E%3Curl%3E%3C/url%3E&rft.eisbn=9781424456550&rft.eisbn_list=9781424456543&rft.eisbn_list=142445655X&rft.eisbn_list=1424456541&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=5414154&rfr_iscdi=true |