{"id":"https://openalex.org/W2115734113","doi":"https://doi.org/10.1109/cvpr.2012.6247870","title":"Multitarget data association with higher-order motion models","display_name":"Multitarget data association with higher-order motion models","publication_year":2012,"publication_date":"2012-06-01","ids":{"openalex":"https://openalex.org/W2115734113","doi":"https://doi.org/10.1109/cvpr.2012.6247870","mag":"2115734113"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2012.6247870","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2012.6247870","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE Conference on Computer Vision and Pattern Recognition","raw_type":"proceedings-article"},"type":"article","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/A5081509021","display_name":"Robert T. Collins","orcid":"https://orcid.org/0000-0001-9062-4252"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"R. T. Collins","raw_affiliation_strings":["Pennsylvania State University, University Park, PA, USA","The Pennsylvania State University, University Park, PA 16802 USA"],"affiliations":[{"raw_affiliation_string":"Pennsylvania State University, University Park, PA, USA","institution_ids":["https://openalex.org/I130769515"]},{"raw_affiliation_string":"The Pennsylvania State University, University Park, PA 16802 USA","institution_ids":["https://openalex.org/I130769515"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5081509021"],"corresponding_institution_ids":["https://openalex.org/I130769515"],"apc_list":null,"apc_paid":null,"fwci":19.8957,"has_fulltext":false,"cited_by_count":127,"citation_normalized_percentile":{"value":0.99430709,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1744","last_page":"1751"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9962999820709229,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9962999820709229,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9933000206947327,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10271","display_name":"Seismic Imaging and Inversion Techniques","score":0.9914000034332275,"subfield":{"id":"https://openalex.org/subfields/1908","display_name":"Geophysics"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/iterated-function","display_name":"Iterated function","score":0.7252174615859985},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5913066267967224},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.5709313750267029},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.5687996745109558},{"id":"https://openalex.org/keywords/data-association","display_name":"Data association","score":0.5291498303413391},{"id":"https://openalex.org/keywords/greedy-algorithm","display_name":"Greedy algorithm","score":0.5265517234802246},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.52186119556427},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.5214961767196655},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.49779629707336426},{"id":"https://openalex.org/keywords/iterative-method","display_name":"Iterative method","score":0.49130386114120483},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.4830234944820404},{"id":"https://openalex.org/keywords/constant","display_name":"Constant (computer programming)","score":0.4644033908843994},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3591623902320862},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.18813556432724},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.13380488753318787},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.08661097288131714}],"concepts":[{"id":"https://openalex.org/C140479938","wikidata":"https://www.wikidata.org/wiki/Q5254619","display_name":"Iterated function","level":2,"score":0.7252174615859985},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5913066267967224},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.5709313750267029},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.5687996745109558},{"id":"https://openalex.org/C2983325608","wikidata":"https://www.wikidata.org/wiki/Q17084606","display_name":"Data association","level":3,"score":0.5291498303413391},{"id":"https://openalex.org/C51823790","wikidata":"https://www.wikidata.org/wiki/Q504353","display_name":"Greedy algorithm","level":2,"score":0.5265517234802246},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.52186119556427},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5214961767196655},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.49779629707336426},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.49130386114120483},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.4830234944820404},{"id":"https://openalex.org/C2777027219","wikidata":"https://www.wikidata.org/wiki/Q1284190","display_name":"Constant (computer programming)","level":2,"score":0.4644033908843994},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3591623902320862},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.18813556432724},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.13380488753318787},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.08661097288131714},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/cvpr.2012.6247870","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2012.6247870","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE Conference on Computer Vision and Pattern Recognition","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.659.2921","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.659.2921","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cse.psu.edu/%7Ercollins/Papers/CollinsCVPR2012.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.675.412","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.675.412","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://vision.cse.psu.edu/courses/Tracking/vlpr12/CollinsCVPR2012.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/W177037875","https://openalex.org/W1554544485","https://openalex.org/W1568122762","https://openalex.org/W1587878450","https://openalex.org/W1966136723","https://openalex.org/W1981908713","https://openalex.org/W2001341021","https://openalex.org/W2014898029","https://openalex.org/W2016135469","https://openalex.org/W2100548006","https://openalex.org/W2104095591","https://openalex.org/W2107401725","https://openalex.org/W2111644456","https://openalex.org/W2124541566","https://openalex.org/W2124781496","https://openalex.org/W2127021804","https://openalex.org/W2138302688","https://openalex.org/W2146688665","https://openalex.org/W2148442626","https://openalex.org/W2168688492","https://openalex.org/W2171243491","https://openalex.org/W2467020497","https://openalex.org/W4239749705","https://openalex.org/W6635241246","https://openalex.org/W6654237837","https://openalex.org/W6676780830"],"related_works":["https://openalex.org/W4387497383","https://openalex.org/W3183948672","https://openalex.org/W3173606202","https://openalex.org/W3110381201","https://openalex.org/W2948807893","https://openalex.org/W2935909890","https://openalex.org/W2778153218","https://openalex.org/W2758277628","https://openalex.org/W1531601525","https://openalex.org/W2084415399"],"abstract_inverted_index":{"We":[0],"present":[1],"an":[2],"iterative":[3],"approximate":[4],"solution":[5,20,65],"to":[6,27,32,44,66],"the":[7,33,56,64,79],"multidimensional":[8],"assignment":[9,70],"problem":[10],"under":[11],"general":[12],"cost":[13],"functions.":[14],"The":[15],"method":[16,80],"maintains":[17],"a":[18,45,67,91],"feasible":[19],"at":[21,41],"every":[22],"step,":[23],"and":[24,86],"is":[25,30],"guaranteed":[26],"converge.":[28],"It":[29],"similar":[31],"iterated":[34],"conditional":[35,58],"modes":[36],"(ICM)":[37],"algorithm,":[38],"but":[39],"applied":[40],"each":[42],"step":[43],"block":[46],"of":[47],"variables":[48],"representing":[49],"correspondences":[50],"between":[51],"two":[52],"adjacent":[53],"frames,":[54],"with":[55,73],"optimal":[57],"mode":[59],"being":[60],"calculated":[61],"exactly":[62],"as":[63],"two-frame":[68],"linear":[69],"problem.":[71],"Experiments":[72],"ground-truthed":[74],"trajectory":[75],"data":[76,84],"show":[77],"that":[78],"outperforms":[81],"both":[82],"network-flow":[83],"association":[85],"greedy":[87],"recursive":[88],"filtering":[89],"using":[90],"constant":[92],"velocity":[93],"motion":[94],"model.":[95]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":11},{"year":2019,"cited_by_count":14},{"year":2018,"cited_by_count":11},{"year":2017,"cited_by_count":13},{"year":2016,"cited_by_count":16},{"year":2015,"cited_by_count":13},{"year":2014,"cited_by_count":17},{"year":2013,"cited_by_count":14},{"year":2012,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}