{"id":"https://openalex.org/W2150452885","doi":"https://doi.org/10.1109/robot.2009.5152731","title":"Tracking groups of people with a multi-model hypothesis tracker","display_name":"Tracking groups of people with a multi-model hypothesis tracker","publication_year":2009,"publication_date":"2009-05-01","ids":{"openalex":"https://openalex.org/W2150452885","doi":"https://doi.org/10.1109/robot.2009.5152731","mag":"2150452885"},"language":"en","primary_location":{"id":"doi:10.1109/robot.2009.5152731","is_oa":false,"landing_page_url":"https://doi.org/10.1109/robot.2009.5152731","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE International Conference on Robotics and Automation","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/A5006112535","display_name":"Buon Kiong Lau","orcid":"https://orcid.org/0000-0002-9203-2629"},"institutions":[{"id":"https://openalex.org/I161046081","display_name":"University of Freiburg","ror":"https://ror.org/0245cg223","country_code":"DE","type":"education","lineage":["https://openalex.org/I161046081"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"B. Lau","raw_affiliation_strings":["Department of Computer Science, University of Freiburg, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Freiburg, Germany","institution_ids":["https://openalex.org/I161046081"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111969299","display_name":"Kai O. Arras","orcid":null},"institutions":[{"id":"https://openalex.org/I161046081","display_name":"University of Freiburg","ror":"https://ror.org/0245cg223","country_code":"DE","type":"education","lineage":["https://openalex.org/I161046081"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"K.O. Arras","raw_affiliation_strings":["Department of Computer Science, University of Freiburg, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Freiburg, Germany","institution_ids":["https://openalex.org/I161046081"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084499878","display_name":"Wolfram Burgard","orcid":"https://orcid.org/0000-0002-5680-6500"},"institutions":[{"id":"https://openalex.org/I161046081","display_name":"University of Freiburg","ror":"https://ror.org/0245cg223","country_code":"DE","type":"education","lineage":["https://openalex.org/I161046081"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"W. Burgard","raw_affiliation_strings":["Department of Computer Science, University of Freiburg, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Freiburg, Germany","institution_ids":["https://openalex.org/I161046081"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I161046081"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":32,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3180","last_page":"3185"},"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":0.9943000078201294,"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":0.9943000078201294,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9929999709129333,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9420999884605408,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/merge","display_name":"Merge (version control)","score":0.8518953323364258},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6915284395217896},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.5726490020751953},{"id":"https://openalex.org/keywords/hausdorff-distance","display_name":"Hausdorff distance","score":0.5667474269866943},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5262740850448608},{"id":"https://openalex.org/keywords/continuation","display_name":"Continuation","score":0.47208094596862793},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.47077107429504395},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4030892550945282},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.08778113126754761}],"concepts":[{"id":"https://openalex.org/C197129107","wikidata":"https://www.wikidata.org/wiki/Q1921621","display_name":"Merge (version control)","level":2,"score":0.8518953323364258},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6915284395217896},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.5726490020751953},{"id":"https://openalex.org/C141898687","wikidata":"https://www.wikidata.org/wiki/Q1501997","display_name":"Hausdorff distance","level":2,"score":0.5667474269866943},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5262740850448608},{"id":"https://openalex.org/C88626702","wikidata":"https://www.wikidata.org/wiki/Q1128903","display_name":"Continuation","level":2,"score":0.47208094596862793},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.47077107429504395},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4030892550945282},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.08778113126754761},{"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},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/robot.2009.5152731","is_oa":false,"landing_page_url":"https://doi.org/10.1109/robot.2009.5152731","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE International Conference on Robotics and Automation","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.231.1667","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.231.1667","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://ais.informatik.uni-freiburg.de/publications/papers/lau09icra.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.700.9919","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.700.9919","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www2.informatik.uni-freiburg.de/%7Earras/papers/lauICRA09.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.44999998807907104,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W2011087880","https://openalex.org/W2037399936","https://openalex.org/W2066832919","https://openalex.org/W2072595688","https://openalex.org/W2076762532","https://openalex.org/W2098556421","https://openalex.org/W2100548006","https://openalex.org/W2107105977","https://openalex.org/W2107800767","https://openalex.org/W2108425682","https://openalex.org/W2111957821","https://openalex.org/W2115672710","https://openalex.org/W2121215404","https://openalex.org/W2125127046","https://openalex.org/W2127923214","https://openalex.org/W2142674933","https://openalex.org/W2164306484","https://openalex.org/W2294153305","https://openalex.org/W2306347658","https://openalex.org/W2913066018","https://openalex.org/W3033479605","https://openalex.org/W4252521233","https://openalex.org/W6678073934","https://openalex.org/W6698306295","https://openalex.org/W6779276871"],"related_works":["https://openalex.org/W1578117154","https://openalex.org/W2542256560","https://openalex.org/W1543936162","https://openalex.org/W1971776229","https://openalex.org/W1971151","https://openalex.org/W2914830601","https://openalex.org/W2766961550","https://openalex.org/W2112263445","https://openalex.org/W1497101000","https://openalex.org/W2054235656"],"abstract_inverted_index":{"People":[0],"in":[1,30,55,88,143,159],"densely":[2],"populated":[3,144],"environments":[4],"typically":[5],"form":[6],"groups":[7,17,66,147],"that":[8,78],"split":[9],"and":[10,27,68,82,92,121,137],"merge.":[11],"In":[12],"this":[13,24],"paper":[14],"we":[15,57],"track":[16],"of":[18,36,63,71,97],"people":[19,38,154],"so":[20],"as":[21,48],"to":[22,73,123],"reflect":[23],"formation":[25],"process":[26],"gain":[28],"efficiency":[29],"situations":[31],"where":[32],"maintaining":[33],"the":[34,44,61,69,98,103,128],"state":[35],"individual":[37],"would":[39],"be":[40],"intractable.":[41],"We":[42],"pose":[43],"group":[45,125],"tracking":[46,146,153],"problem":[47,54],"a":[49,89,113,118,135,138,162],"recursive":[50],"multi-hypothesis":[51],"model":[52,120],"selection":[53],"which":[56],"hypothesize":[58],"over":[59],"both,":[60],"partitioning":[62],"tracks":[64,74,126],"into":[65],"(models)":[67],"association":[70],"observations":[72],"(assignments).":[75],"Model":[76],"hypotheses":[77],"include":[79],"split,":[80],"merge,":[81],"continuation":[83],"events":[84],"are":[85,107],"first":[86],"generated":[87],"data-driven":[90],"manner":[91],"then":[93],"validated":[94],"by":[95,109],"means":[96],"assignment":[99],"probabilities":[100],"conditioned":[101],"on":[102,161],"respective":[104],"model.":[105],"Observations":[106],"found":[108],"clustering":[110],"points":[111],"from":[112],"laser":[114],"range":[115],"finder":[116],"given":[117],"background":[119],"associated":[122],"existing":[124],"using":[127],"minimum":[129],"average":[130],"Hausdorff":[131],"distance.":[132],"Experiments":[133],"with":[134],"stationary":[136],"moving":[139],"platform":[140],"show":[141],"that,":[142],"environments,":[145],"is":[148],"clearly":[149],"more":[150],"efficient":[151],"than":[152],"separately.":[155],"Our":[156],"system":[157],"runs":[158],"real-time":[160],"typical":[163],"desktop":[164],"computer.":[165]},"counts_by_year":[{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":3},{"year":2018,"cited_by_count":1},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":5},{"year":2013,"cited_by_count":3},{"year":2012,"cited_by_count":5}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}