Tracking deformable objects in geospatial applications
In this paper we describe a novel approach for change detection of moving deformable objects. We assume that each object is represented as a closed polygon (convex or concave). First, we use differential snakes to track the object outline between two different frames. Next, we examine the geometric...
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| creator | Gyftakis, S. Agouris, P. Stefanidis, A. |
| description | In this paper we describe a novel approach for change detection of moving deformable objects. We assume that each object is represented as a closed polygon (convex or concave). First, we use differential snakes to track the object outline between two different frames. Next, we examine the geometric properties (area moments and principal axes) of these two polygons and we estimate their changes (translation, rotation, area expanded or contracted). Additionally, using results from invariant moments theory we compute a similarity index among different instances of an object's history. This information is used to update geospatial databases and to support complex analysis. Experimental results on real imagery illustrate the capabilities of our approach. |
| doi_str_mv | 10.1109/ICIP.2004.1421630 |
| format | Conference Proceeding |
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We assume that each object is represented as a closed polygon (convex or concave). First, we use differential snakes to track the object outline between two different frames. Next, we examine the geometric properties (area moments and principal axes) of these two polygons and we estimate their changes (translation, rotation, area expanded or contracted). Additionally, using results from invariant moments theory we compute a similarity index among different instances of an object's history. This information is used to update geospatial databases and to support complex analysis. Experimental results on real imagery illustrate the capabilities of our approach.</description><identifier>ISSN: 1522-4880</identifier><identifier>ISBN: 0780385543</identifier><identifier>ISBN: 9780780385542</identifier><identifier>EISSN: 2381-8549</identifier><identifier>DOI: 10.1109/ICIP.2004.1421630</identifier><language>eng</language><publisher>Piscataway NJ: IEEE</publisher><subject>Active contours ; Applied sciences ; Artificial intelligence ; Computational Intelligence Society ; Computer science; control theory; systems ; Deformable models ; Exact sciences and technology ; Information science ; Information systems ; Modems ; Monitoring ; Object detection ; Pattern recognition. Digital image processing. Computational geometry ; Shape</subject><ispartof>2004 International Conference on Image Processing, 2004. 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Experimental results on real imagery illustrate the capabilities of our approach.</description><subject>Active contours</subject><subject>Applied sciences</subject><subject>Artificial intelligence</subject><subject>Computational Intelligence Society</subject><subject>Computer science; control theory; systems</subject><subject>Deformable models</subject><subject>Exact sciences and technology</subject><subject>Information science</subject><subject>Information systems</subject><subject>Modems</subject><subject>Monitoring</subject><subject>Object detection</subject><subject>Pattern recognition. Digital image processing. Computational geometry</subject><subject>Shape</subject><issn>1522-4880</issn><issn>2381-8549</issn><isbn>0780385543</isbn><isbn>9780780385542</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2004</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNpFkDtrw0AQhI88ILaTHxDSqEkpZfdeuiuDycNgSAqnNqvVyZwjS0KnJv8-AgdSzcB8DMwIcY9QIIJ_2qw3n4UE0AVqiVbBhVhI5TB3RvtLsYTSgXLGaHUlFmikzLVzcCOWKR0BJKDChbC7kfg7doesDk0_nqhqQ9ZXx8BTymKXHUKfBpoitRkNQxt59n2XbsV1Q20Kd3-6El-vL7v1e779eNusn7d5lGCm3BKpyvoK2Vgua_aBbWOdUr5G3ZTItQmhKVkaVXFNNkCp2Blv5z1AntVKPJ57B0pMbTNSxzHthzGeaPzZY2kRvdcz93DmYgjhPz7_on4BmtdUng</recordid><startdate>2004</startdate><enddate>2004</enddate><creator>Gyftakis, S.</creator><creator>Agouris, P.</creator><creator>Stefanidis, A.</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope><scope>IQODW</scope></search><sort><creationdate>2004</creationdate><title>Tracking deformable objects in geospatial applications</title><author>Gyftakis, S. ; Agouris, P. ; Stefanidis, A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i205t-6aa3b69b1c56c7dc9ec6f68339d14f71cd5eef7c253bcda6e073c85962160a9c3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2004</creationdate><topic>Active contours</topic><topic>Applied sciences</topic><topic>Artificial intelligence</topic><topic>Computational Intelligence Society</topic><topic>Computer science; control theory; systems</topic><topic>Deformable models</topic><topic>Exact sciences and technology</topic><topic>Information science</topic><topic>Information systems</topic><topic>Modems</topic><topic>Monitoring</topic><topic>Object detection</topic><topic>Pattern recognition. Digital image processing. Computational geometry</topic><topic>Shape</topic><toplevel>online_resources</toplevel><creatorcontrib>Gyftakis, S.</creatorcontrib><creatorcontrib>Agouris, P.</creatorcontrib><creatorcontrib>Stefanidis, 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>Pascal-Francis</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Gyftakis, S.</au><au>Agouris, P.</au><au>Stefanidis, A.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Tracking deformable objects in geospatial applications</atitle><btitle>2004 International Conference on Image Processing, 2004. ICIP '04</btitle><stitle>ICIP</stitle><date>2004</date><risdate>2004</risdate><volume>4</volume><spage>2579</spage><epage>2582 Vol. 4</epage><pages>2579-2582 Vol. 4</pages><issn>1522-4880</issn><eissn>2381-8549</eissn><isbn>0780385543</isbn><isbn>9780780385542</isbn><abstract>In this paper we describe a novel approach for change detection of moving deformable objects. We assume that each object is represented as a closed polygon (convex or concave). First, we use differential snakes to track the object outline between two different frames. Next, we examine the geometric properties (area moments and principal axes) of these two polygons and we estimate their changes (translation, rotation, area expanded or contracted). Additionally, using results from invariant moments theory we compute a similarity index among different instances of an object's history. This information is used to update geospatial databases and to support complex analysis. Experimental results on real imagery illustrate the capabilities of our approach.</abstract><cop>Piscataway NJ</cop><pub>IEEE</pub><doi>10.1109/ICIP.2004.1421630</doi></addata></record> |
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| identifier | ISSN: 1522-4880 |
| ispartof | 2004 International Conference on Image Processing, 2004. ICIP '04, 2004, Vol.4, p.2579-2582 Vol. 4 |
| issn | 1522-4880 2381-8549 |
| language | eng |
| recordid | cdi_pascalfrancis_primary_17611994 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Active contours Applied sciences Artificial intelligence Computational Intelligence Society Computer science control theory systems Deformable models Exact sciences and technology Information science Information systems Modems Monitoring Object detection Pattern recognition. Digital image processing. Computational geometry Shape |
| title | Tracking deformable objects in geospatial applications |
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