Visual System Based on Artificial Retina for Motion Detection
We present a bioinspired model for detecting spatiotemporal features based on artificial retina response models. Event-driven processing is implemented using four kinds of cells encoding image contrast and temporal information. We have evaluated how the accuracy of motion processing depends on local...
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| Veröffentlicht in: | IEEE transactions on cybernetics 2009-06, Vol.39 (3), p.752-762 |
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| container_end_page | 762 |
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| container_title | IEEE transactions on cybernetics |
| container_volume | 39 |
| creator | Barranco, F. Diaz, J. Ros, E. del Pino, B. |
| description | We present a bioinspired model for detecting spatiotemporal features based on artificial retina response models. Event-driven processing is implemented using four kinds of cells encoding image contrast and temporal information. We have evaluated how the accuracy of motion processing depends on local contrast by using a multiscale and rank-order coding scheme to select the most important cues from retinal inputs. We have also developed some alternatives by integrating temporal feature results and obtained a new improved bioinspired matching algorithm with high stability, low error and low cost. Finally, we define a dynamic and versatile multimodal attention operator with which the system is driven to focus on different target features such as motion, colors, and textures. |
| doi_str_mv | 10.1109/TSMCB.2008.2009067 |
| format | Article |
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(IEEE) 2009</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c380t-e879bf777bfcf45fee61653edcf3e8900d206d3ea432e954b0890182c25037893</citedby><cites>FETCH-LOGICAL-c380t-e879bf777bfcf45fee61653edcf3e8900d206d3ea432e954b0890182c25037893</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/4812007$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,27924,27925,54758</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/4812007$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/19362896$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Barranco, F.</creatorcontrib><creatorcontrib>Diaz, J.</creatorcontrib><creatorcontrib>Ros, E.</creatorcontrib><creatorcontrib>del Pino, B.</creatorcontrib><title>Visual System Based on Artificial Retina for Motion Detection</title><title>IEEE transactions on cybernetics</title><addtitle>TSMCB</addtitle><addtitle>IEEE Trans Syst Man Cybern B Cybern</addtitle><description>We present a bioinspired model for detecting spatiotemporal features based on artificial retina response models. Event-driven processing is implemented using four kinds of cells encoding image contrast and temporal information. We have evaluated how the accuracy of motion processing depends on local contrast by using a multiscale and rank-order coding scheme to select the most important cues from retinal inputs. We have also developed some alternatives by integrating temporal feature results and obtained a new improved bioinspired matching algorithm with high stability, low error and low cost. Finally, we define a dynamic and versatile multimodal attention operator with which the system is driven to focus on different target features such as motion, colors, and textures.</description><subject>Algorithms</subject><subject>Artificial Intelligence</subject><subject>Artificial retina</subject><subject>bioinspired vision</subject><subject>Biological system modeling</subject><subject>Biology computing</subject><subject>block matching</subject><subject>Computer architecture</subject><subject>Cost function</subject><subject>Cybernetics - methods</subject><subject>Image Enhancement - methods</subject><subject>Image Processing, Computer-Assisted - methods</subject><subject>Models, Neurological</subject><subject>Motion</subject><subject>Motion detection</subject><subject>Motion estimation</subject><subject>motion processing</subject><subject>multiscale motion estimation</subject><subject>rank-order coding</subject><subject>Retina</subject><subject>Retina - physiology</subject><subject>retinomorphic chip</subject><subject>Spatiotemporal phenomena</subject><subject>Stability</subject><subject>Time Factors</subject><subject>Visual system</subject><issn>1083-4419</issn><issn>2168-2267</issn><issn>1941-0492</issn><issn>2168-2275</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2009</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><sourceid>EIF</sourceid><recordid>eNp9kUlLA0EQhRtRTIz-AQUZPOhpYm_Ty8FDEldIEEz02sxSDR2STJyeOeTf22MGBQ9eqop-Xz3oegidEzwkBOvbxXw2GQ8pxqotGgt5gPpEcxJjrulhmLFiMedE99CJ90vcQloeox7RTFClRR_dfTjfpKtovvM1rKNx6qGIyk00qmpnXe6C9Aa126SRLatoVtYuiPdQQ95Op-jIpisPZ10foPfHh8XkOZ6-Pr1MRtM4ZwrXMSipMyulzGxueWIBBBEJgyK3DJTGuKBYFAxSzijohGc4PBJFc5pgJpVmA3Sz991W5WcDvjZr53NYrdINlI03SmiViHCAQF7_SwpJiBaaBfDqD7gsm2oTfmFUIjnjSUIDRPdQXpXeV2DNtnLrtNoZgk2bgfnOwLQZmC6DsHTZOTfZGorfle7oAbjYAw4AfmSuSHCQ7AtKNoh_</recordid><startdate>20090601</startdate><enddate>20090601</enddate><creator>Barranco, F.</creator><creator>Diaz, J.</creator><creator>Ros, E.</creator><creator>del Pino, B.</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>7TB</scope><scope>8FD</scope><scope>F28</scope><scope>FR3</scope><scope>H8D</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>7X8</scope><scope>7TK</scope></search><sort><creationdate>20090601</creationdate><title>Visual System Based on Artificial Retina for Motion Detection</title><author>Barranco, F. ; Diaz, J. ; Ros, E. ; del Pino, B.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c380t-e879bf777bfcf45fee61653edcf3e8900d206d3ea432e954b0890182c25037893</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2009</creationdate><topic>Algorithms</topic><topic>Artificial Intelligence</topic><topic>Artificial retina</topic><topic>bioinspired vision</topic><topic>Biological system modeling</topic><topic>Biology computing</topic><topic>block matching</topic><topic>Computer architecture</topic><topic>Cost function</topic><topic>Cybernetics - methods</topic><topic>Image Enhancement - methods</topic><topic>Image Processing, Computer-Assisted - methods</topic><topic>Models, Neurological</topic><topic>Motion</topic><topic>Motion detection</topic><topic>Motion estimation</topic><topic>motion processing</topic><topic>multiscale motion estimation</topic><topic>rank-order coding</topic><topic>Retina</topic><topic>Retina - physiology</topic><topic>retinomorphic chip</topic><topic>Spatiotemporal phenomena</topic><topic>Stability</topic><topic>Time Factors</topic><topic>Visual system</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Barranco, F.</creatorcontrib><creatorcontrib>Diaz, J.</creatorcontrib><creatorcontrib>Ros, E.</creatorcontrib><creatorcontrib>del Pino, B.</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>MEDLINE - Academic</collection><collection>Neurosciences Abstracts</collection><jtitle>IEEE transactions on cybernetics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Barranco, F.</au><au>Diaz, J.</au><au>Ros, E.</au><au>del Pino, B.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Visual System Based on Artificial Retina for Motion Detection</atitle><jtitle>IEEE transactions on cybernetics</jtitle><stitle>TSMCB</stitle><addtitle>IEEE Trans Syst Man Cybern B Cybern</addtitle><date>2009-06-01</date><risdate>2009</risdate><volume>39</volume><issue>3</issue><spage>752</spage><epage>762</epage><pages>752-762</pages><issn>1083-4419</issn><issn>2168-2267</issn><eissn>1941-0492</eissn><eissn>2168-2275</eissn><coden>ITSCFI</coden><abstract>We present a bioinspired model for detecting spatiotemporal features based on artificial retina response models. Event-driven processing is implemented using four kinds of cells encoding image contrast and temporal information. We have evaluated how the accuracy of motion processing depends on local contrast by using a multiscale and rank-order coding scheme to select the most important cues from retinal inputs. We have also developed some alternatives by integrating temporal feature results and obtained a new improved bioinspired matching algorithm with high stability, low error and low cost. Finally, we define a dynamic and versatile multimodal attention operator with which the system is driven to focus on different target features such as motion, colors, and textures.</abstract><cop>United States</cop><pub>IEEE</pub><pmid>19362896</pmid><doi>10.1109/TSMCB.2008.2009067</doi><tpages>11</tpages></addata></record> |
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| source | IEEE Electronic Library (IEL) |
| subjects | Algorithms Artificial Intelligence Artificial retina bioinspired vision Biological system modeling Biology computing block matching Computer architecture Cost function Cybernetics - methods Image Enhancement - methods Image Processing, Computer-Assisted - methods Models, Neurological Motion Motion detection Motion estimation motion processing multiscale motion estimation rank-order coding Retina Retina - physiology retinomorphic chip Spatiotemporal phenomena Stability Time Factors Visual system |
| title | Visual System Based on Artificial Retina for Motion Detection |
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