Kernel and Feature Selection for Visible and Infrared based Obstacle Recognition
In this article we propose a fusion model at data-level based on a linear combination of kernels. These kernels functions will be evaluated on disjoint entries, on the signature acquired from visible respective infrared spectrum. Therefore, we have to choose the proper numeric signature for the visi...
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| creator | Apatean, Anca Rogozan, Alexandrina Bensrhair, Abdelaziz |
| description | In this article we propose a fusion model at data-level based on a linear combination of kernels. These kernels functions will be evaluated on disjoint entries, on the signature acquired from visible respective infrared spectrum. Therefore, we have to choose the proper numeric signature for the visible and for the infrared images. In order to retain just the best suited features, different feature extraction and feature selection algorithms have been investigated. In this way, important information can be achieved in a small number of coefficients, implying thus a significant reduction of the computation time. Our purpose is to develop the obstacle recognition module and to examine if a visible-infrared fusion is efficient for this task. |
| doi_str_mv | 10.1109/ITSC.2008.4732711 |
| format | Conference Proceeding |
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Our purpose is to develop the obstacle recognition module and to examine if a visible-infrared fusion is efficient for this task.</description><subject>Feature extraction</subject><subject>Infrared spectra</subject><subject>Kernel</subject><subject>Laser radar</subject><subject>Object detection</subject><subject>Radar detection</subject><subject>Real time systems</subject><subject>Roads</subject><subject>Support vector machine classification</subject><subject>Support vector machines</subject><issn>2153-0009</issn><issn>2153-0017</issn><isbn>9781424421114</isbn><isbn>142442111X</isbn><isbn>9781424421121</isbn><isbn>1424421128</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2008</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNpVkM1OwzAQhM1PJUrJAyAueYEU79pO7COqKERUKqKFa2Una2QUEuSEA29PChUSl1lpvp05DGOXwOcA3FyX281ijpzruSwEFgBHLDGFBolSIgDCMZsiKJFxDsXJPwby9I9xM2Hn-xrD0eT6jCV9_zbaXCoxBqbs8YFiS01q2zpdkh0-I6UbaqgaQtemvovpS-iDa-jno2x9tJHq1Nl-1LXrB1uN7Imq7rUN-8wFm3jb9JQc7ow9L2-3i_tstb4rFzerLEChhqzQHnN0ApVC9EJh5SSg56Rr7y3UzuRcOp6DBgeCSFUe0JDSTuQ1jpvM2NVvbyCi3UcM7zZ-7Q5jiW-joVWP</recordid><startdate>200810</startdate><enddate>200810</enddate><creator>Apatean, Anca</creator><creator>Rogozan, Alexandrina</creator><creator>Bensrhair, Abdelaziz</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>200810</creationdate><title>Kernel and Feature Selection for Visible and Infrared based Obstacle Recognition</title><author>Apatean, Anca ; Rogozan, Alexandrina ; Bensrhair, Abdelaziz</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-78f262b325522f352cb412f0e8dffa1db9604b06181b13ee5cf129e58b36d2473</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2008</creationdate><topic>Feature extraction</topic><topic>Infrared spectra</topic><topic>Kernel</topic><topic>Laser radar</topic><topic>Object detection</topic><topic>Radar detection</topic><topic>Real time systems</topic><topic>Roads</topic><topic>Support vector machine classification</topic><topic>Support vector machines</topic><toplevel>online_resources</toplevel><creatorcontrib>Apatean, Anca</creatorcontrib><creatorcontrib>Rogozan, Alexandrina</creatorcontrib><creatorcontrib>Bensrhair, Abdelaziz</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>Apatean, Anca</au><au>Rogozan, Alexandrina</au><au>Bensrhair, Abdelaziz</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Kernel and Feature Selection for Visible and Infrared based Obstacle Recognition</atitle><btitle>2008 11th International IEEE Conference on Intelligent Transportation Systems</btitle><stitle>ITSC</stitle><date>2008-10</date><risdate>2008</risdate><spage>1130</spage><epage>1135</epage><pages>1130-1135</pages><issn>2153-0009</issn><eissn>2153-0017</eissn><isbn>9781424421114</isbn><isbn>142442111X</isbn><eisbn>9781424421121</eisbn><eisbn>1424421128</eisbn><abstract>In this article we propose a fusion model at data-level based on a linear combination of kernels. 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| ispartof | 2008 11th International IEEE Conference on Intelligent Transportation Systems, 2008, p.1130-1135 |
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| language | eng |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Feature extraction Infrared spectra Kernel Laser radar Object detection Radar detection Real time systems Roads Support vector machine classification Support vector machines |
| title | Kernel and Feature Selection for Visible and Infrared based Obstacle Recognition |
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