{"id":"https://openalex.org/W1993037067","doi":"https://doi.org/10.1109/cvpr.2009.5206541","title":"Motion pattern interpretation and detection for tracking moving vehicles in airborne video","display_name":"Motion pattern interpretation and detection for tracking moving vehicles in airborne video","publication_year":2009,"publication_date":"2009-06-01","ids":{"openalex":"https://openalex.org/W1993037067","doi":"https://doi.org/10.1109/cvpr.2009.5206541","mag":"1993037067"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2009.5206541","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2009.5206541","pdf_url":null,"source":{"id":"https://openalex.org/S4363607795","display_name":"2009 IEEE Conference on Computer Vision and Pattern Recognition","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE Conference on Computer Vision and Pattern Recognition","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5055944639","display_name":"Qian Yu","orcid":"https://orcid.org/0000-0002-6224-5607"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qian Yu","raw_affiliation_strings":["Institute for Robotics and Intelligent Systems, University of Southern California, Los Angeles, CA, USA","Inst. for Robot. & Intell. Syst., Univ. of Southern California, Los Angeles, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Robotics and Intelligent Systems, University of Southern California, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I1174212"]},{"raw_affiliation_string":"Inst. for Robot. & Intell. Syst., Univ. of Southern California, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006918685","display_name":"G\u00e9rard Medioni","orcid":null},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gerard Medioni","raw_affiliation_strings":["Institute for Robotics and Intelligent Systems, University of Southern California, Los Angeles, CA, USA","Inst. for Robot. & Intell. Syst., Univ. of Southern California, Los Angeles, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Robotics and Intelligent Systems, University of Southern California, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I1174212"]},{"raw_affiliation_string":"Inst. for Robot. & Intell. Syst., Univ. of Southern California, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I1174212"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I1174212"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":50,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2671","last_page":"2678"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9968000054359436,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9952999949455261,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.8005869388580322},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7638748288154602},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7171913981437683},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.6169732213020325},{"id":"https://openalex.org/keywords/parallax","display_name":"Parallax","score":0.6135701537132263},{"id":"https://openalex.org/keywords/optical-flow","display_name":"Optical flow","score":0.6005054712295532},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.5504084229469299},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.5448378324508667},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5337790846824646},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.49941396713256836},{"id":"https://openalex.org/keywords/motion-estimation","display_name":"Motion estimation","score":0.4122553765773773},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.16241466999053955}],"concepts":[{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.8005869388580322},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7638748288154602},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7171913981437683},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.6169732213020325},{"id":"https://openalex.org/C15759828","wikidata":"https://www.wikidata.org/wiki/Q165074","display_name":"Parallax","level":2,"score":0.6135701537132263},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.6005054712295532},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.5504084229469299},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.5448378324508667},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5337790846824646},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.49941396713256836},{"id":"https://openalex.org/C10161872","wikidata":"https://www.wikidata.org/wiki/Q557891","display_name":"Motion estimation","level":2,"score":0.4122553765773773},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.16241466999053955},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/cvpr.2009.5206541","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2009.5206541","pdf_url":null,"source":{"id":"https://openalex.org/S4363607795","display_name":"2009 IEEE Conference on Computer Vision and Pattern Recognition","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE Conference on Computer Vision and Pattern Recognition","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.310.43","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.310.43","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://iris.usc.edu/Outlines/papers/2009/yu-medioni-cvpr09.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1482815597","https://openalex.org/W1516887802","https://openalex.org/W2087061417","https://openalex.org/W2087399108","https://openalex.org/W2096250715","https://openalex.org/W2100519657","https://openalex.org/W2108404684","https://openalex.org/W2113050750","https://openalex.org/W2120350085","https://openalex.org/W2121153043","https://openalex.org/W2125315716","https://openalex.org/W2139695834","https://openalex.org/W2140137670","https://openalex.org/W2150928070","https://openalex.org/W2157344637","https://openalex.org/W2159669057","https://openalex.org/W2164047143","https://openalex.org/W2222512263","https://openalex.org/W3030910590","https://openalex.org/W6628681060","https://openalex.org/W6630825005","https://openalex.org/W6672512439","https://openalex.org/W6675206091","https://openalex.org/W6676832264","https://openalex.org/W6680598823","https://openalex.org/W6683943757"],"related_works":["https://openalex.org/W2310668644","https://openalex.org/W2010112831","https://openalex.org/W2329110763","https://openalex.org/W4307478549","https://openalex.org/W42146583","https://openalex.org/W3034145901","https://openalex.org/W2167098510","https://openalex.org/W2030154815","https://openalex.org/W2051121715","https://openalex.org/W1929254672"],"abstract_inverted_index":{"Detection":[0],"and":[1,24,90,113,145,190],"tracking":[2,146],"of":[3,59,147],"moving":[4,45,115,130],"vehicles":[5,46,131],"in":[6,47,64,95,99,107,132,140,151,166,175,181],"airborne":[7,48,100,134,182],"videos":[8],"is":[9,40,157],"a":[10,41,55,60,120],"challenging":[11],"problem.":[12],"Many":[13],"approaches":[14],"have":[15],"been":[16,31],"proposed":[17],"to":[18,33,81,88,119,142,159],"improve":[19],"motion":[20,37,62,93,108,125],"segmentation":[21],"on":[22],"frame-by-frame":[23],"pixel-by-pixel":[25],"bases,":[26],"however,":[27],"little":[28],"attention":[29],"has":[30],"paid":[32],"analyze":[34,103],"the":[35,83,104,152,167,176],"long-term":[36],"pattern,":[38],"which":[39,117,162],"distinctive":[42],"property":[43],"for":[44,123],"videos.":[49,135],"In":[50],"this":[51,155],"paper,":[52],"we":[53,102],"provide":[54],"straightforward":[56],"geometric":[57],"interpretation":[58],"general":[61],"pattern":[63],"4D":[65,96],"space":[66],"(x,":[67],"y,":[68],"v":[69,74],"<sub":[70,75],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[71,76],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">x</sub>":[72],",":[73],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">y</sub>":[77],").":[78],"We":[79],"propose":[80],"use":[82],"tensor":[84],"voting":[85],"computational":[86],"framework":[87],"detect":[89],"segment":[91],"such":[92,184],"patterns":[94,109,126],"space.":[97],"Specifically,":[98],"videos,":[101,183],"essential":[105],"difference":[106],"caused":[110],"by":[111,129,197],"parallax":[112],"independent":[114],"objects,":[116],"leads":[118],"practical":[121],"method":[122],"segmenting":[124],"(flows)":[127],"created":[128],"stabilized":[133],"The":[136],"flows":[137],"are":[138],"used":[139],"turn":[141],"facilitate":[143],"detection":[144],"each":[148],"individual":[149],"object":[150],"flow.":[153],"Conceptually,":[154],"approach":[156],"similar":[158],"\u201ctrack-before-detect\u201d":[160],"techniques,":[161],"involves":[163],"temporal":[164],"information":[165],"process":[168],"as":[169,171,185],"early":[170],"possible.":[172],"As":[173],"shown":[174],"experiments,":[177],"many":[178],"difficult":[179],"cases":[180],"parallax,":[186],"noisy":[187],"background":[188],"modeling":[189],"long":[191],"term":[192],"occlusions,":[193],"can":[194],"be":[195],"addressed":[196],"our":[198],"approach.":[199]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":8},{"year":2013,"cited_by_count":8},{"year":2012,"cited_by_count":4}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}