Homographic line generation and transformation technique for dynamic object association
Object association among multiple cameras is an important capability for maintaining consistent view of surroundings. This is necessary in many applications such as tracking and surveillance. In this paper, we present a dynamic homographic line generation technique supporting the camera movement for...
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creator | Shung Han Cho Sangjin Hong We-Duke Cho |
description | Object association among multiple cameras is an important capability for maintaining consistent view of surroundings. This is necessary in many applications such as tracking and surveillance. In this paper, we present a dynamic homographic line generation technique supporting the camera movement for object association in the multiple visual sensors network. The conventional method uses the globally defined homographic lines or the feature based methods for the object association. However, these methods restrict the camera movement (i.e., panning, tilting and zooming) required for efficient and effective association in the autonomous surveillance system. The proposed method uses the table based compensation for non-ideal camera parameters to support the camera movement. Lastly, two possible application models are simulated with the proposed technique. |
doi_str_mv | 10.1109/MLSP.2008.4685492 |
format | Conference Proceeding |
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This is necessary in many applications such as tracking and surveillance. In this paper, we present a dynamic homographic line generation technique supporting the camera movement for object association in the multiple visual sensors network. The conventional method uses the globally defined homographic lines or the feature based methods for the object association. However, these methods restrict the camera movement (i.e., panning, tilting and zooming) required for efficient and effective association in the autonomous surveillance system. The proposed method uses the table based compensation for non-ideal camera parameters to support the camera movement. 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This is necessary in many applications such as tracking and surveillance. In this paper, we present a dynamic homographic line generation technique supporting the camera movement for object association in the multiple visual sensors network. The conventional method uses the globally defined homographic lines or the feature based methods for the object association. However, these methods restrict the camera movement (i.e., panning, tilting and zooming) required for efficient and effective association in the autonomous surveillance system. The proposed method uses the table based compensation for non-ideal camera parameters to support the camera movement. Lastly, two possible application models are simulated with the proposed technique.</description><subject>Acoustic distortion</subject><subject>Acoustic noise</subject><subject>Acoustic sensors</subject><subject>Application software</subject><subject>Cameras</subject><subject>Labeling</subject><subject>Lenses</subject><subject>Reverberation</subject><subject>Surveillance</subject><subject>Target tracking</subject><issn>1551-2541</issn><issn>2378-928X</issn><isbn>9781424423750</isbn><isbn>1424423759</isbn><isbn>1424423767</isbn><isbn>9781424423767</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2008</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNo1UEtOwzAUND-JUnoAxMYXSLH97NheoopSpCCQAMGucpzn1lXjlCQsensiWmYz0vwWQ8gNZ1POmb17Lt5ep4IxM5W5UdKKE3LFpZBSgM71KRkNbDIrzNcZmVht_j3FzsmIK8UzoSS_JJOu27ABUgG3bEQ-F03drFq3W0dPtzEhXWHC1vWxSdSlivatS11o2vog9ejXKX7_IB00Wu2Tq4diU27Q99R1XePjX_CaXAS37XBy5DH5mD-8zxZZ8fL4NLsvssi16rOylAClzwNC7sEwXXEMEjXmIEDlTGnjIDhRehV80OAEq6yWFjiTCJWAMbk97EZEXO7aWLt2vzx-BL-fHlff</recordid><startdate>200810</startdate><enddate>200810</enddate><creator>Shung Han Cho</creator><creator>Sangjin Hong</creator><creator>We-Duke Cho</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>Homographic line generation and transformation technique for dynamic object association</title><author>Shung Han Cho ; Sangjin Hong ; We-Duke Cho</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-bb433bc6fe36c3807d1ef4e7e6323560578a3fa2bc5fcf73a20d97493104e3d23</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2008</creationdate><topic>Acoustic distortion</topic><topic>Acoustic noise</topic><topic>Acoustic sensors</topic><topic>Application software</topic><topic>Cameras</topic><topic>Labeling</topic><topic>Lenses</topic><topic>Reverberation</topic><topic>Surveillance</topic><topic>Target tracking</topic><toplevel>online_resources</toplevel><creatorcontrib>Shung Han Cho</creatorcontrib><creatorcontrib>Sangjin Hong</creatorcontrib><creatorcontrib>We-Duke Cho</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>Shung Han Cho</au><au>Sangjin Hong</au><au>We-Duke Cho</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Homographic line generation and transformation technique for dynamic object association</atitle><btitle>2008 IEEE Workshop on Machine Learning for Signal Processing</btitle><stitle>MLSP</stitle><date>2008-10</date><risdate>2008</risdate><spage>273</spage><epage>278</epage><pages>273-278</pages><issn>1551-2541</issn><eissn>2378-928X</eissn><isbn>9781424423750</isbn><isbn>1424423759</isbn><eisbn>1424423767</eisbn><eisbn>9781424423767</eisbn><abstract>Object association among multiple cameras is an important capability for maintaining consistent view of surroundings. This is necessary in many applications such as tracking and surveillance. In this paper, we present a dynamic homographic line generation technique supporting the camera movement for object association in the multiple visual sensors network. The conventional method uses the globally defined homographic lines or the feature based methods for the object association. However, these methods restrict the camera movement (i.e., panning, tilting and zooming) required for efficient and effective association in the autonomous surveillance system. The proposed method uses the table based compensation for non-ideal camera parameters to support the camera movement. Lastly, two possible application models are simulated with the proposed technique.</abstract><pub>IEEE</pub><doi>10.1109/MLSP.2008.4685492</doi><tpages>6</tpages></addata></record> |
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subjects | Acoustic distortion Acoustic noise Acoustic sensors Application software Cameras Labeling Lenses Reverberation Surveillance Target tracking |
title | Homographic line generation and transformation technique for dynamic object association |
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