{"id":"https://openalex.org/W2005591481","doi":"https://doi.org/10.1109/isbi.2013.6556560","title":"Keeping count: Leveraging temporal context to count heavily overlapping objects","display_name":"Keeping count: Leveraging temporal context to count heavily overlapping objects","publication_year":2013,"publication_date":"2013-04-01","ids":{"openalex":"https://openalex.org/W2005591481","doi":"https://doi.org/10.1109/isbi.2013.6556560","mag":"2005591481"},"language":"en","primary_location":{"id":"doi:10.1109/isbi.2013.6556560","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2013.6556560","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE 10th International Symposium on Biomedical Imaging","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/A5051850279","display_name":"Luca Fiaschi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Luca Fiaschi","raw_affiliation_strings":["HCI, IWR, Heidelberg, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"HCI, IWR, Heidelberg, Germany","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007181048","display_name":"Konstantin Gregor","orcid":"https://orcid.org/0000-0003-3513-3607"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gregor Konstantin","raw_affiliation_strings":["HCI, IWR, Heidelberg, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"HCI, IWR, Heidelberg, Germany","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030499270","display_name":"Bruno Afonso","orcid":null},"institutions":[{"id":"https://openalex.org/I1344073410","display_name":"Howard Hughes Medical Institute","ror":"https://ror.org/006w34k90","country_code":"US","type":"facility","lineage":["https://openalex.org/I1344073410"]},{"id":"https://openalex.org/I195573530","display_name":"Janelia Research Campus","ror":"https://ror.org/013sk6x84","country_code":"US","type":"facility","lineage":["https://openalex.org/I1344073410","https://openalex.org/I195573530"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bruno Afonso","raw_affiliation_strings":["HHMI Janelia Farm, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"HHMI Janelia Farm, USA","institution_ids":["https://openalex.org/I1344073410","https://openalex.org/I195573530"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059140736","display_name":"Marta Zlatic","orcid":"https://orcid.org/0000-0002-3149-2250"},"institutions":[{"id":"https://openalex.org/I1344073410","display_name":"Howard Hughes Medical Institute","ror":"https://ror.org/006w34k90","country_code":"US","type":"facility","lineage":["https://openalex.org/I1344073410"]},{"id":"https://openalex.org/I195573530","display_name":"Janelia Research Campus","ror":"https://ror.org/013sk6x84","country_code":"US","type":"facility","lineage":["https://openalex.org/I1344073410","https://openalex.org/I195573530"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Marta Zlatic","raw_affiliation_strings":["HHMI Janelia Farm, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"HHMI Janelia Farm, USA","institution_ids":["https://openalex.org/I1344073410","https://openalex.org/I195573530"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020048224","display_name":"Fred A. Hamprecht","orcid":"https://orcid.org/0000-0003-4148-5043"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fred A. Hamprecht","raw_affiliation_strings":["HCI, IWR, Heidelberg, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"HCI, IWR, Heidelberg, Germany","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.2472,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.8277698,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"5","issue":null,"first_page":"656","last_page":"659"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":1.0,"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":1.0,"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":0.9979000091552734,"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":0.996399998664856,"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/computer-science","display_name":"Computer science","score":0.7629132866859436},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.7495735287666321},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.6845487356185913},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6526704430580139},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5838935375213623},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.530240535736084},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5184004306793213},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.478523850440979},{"id":"https://openalex.org/keywords/approximate-inference","display_name":"Approximate inference","score":0.47736072540283203},{"id":"https://openalex.org/keywords/graphical-model","display_name":"Graphical model","score":0.47583866119384766},{"id":"https://openalex.org/keywords/context-model","display_name":"Context model","score":0.4489330053329468},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.42521244287490845},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4211939871311188},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34889814257621765},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3350452780723572},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.2935820519924164}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7629132866859436},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.7495735287666321},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.6845487356185913},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6526704430580139},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5838935375213623},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.530240535736084},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5184004306793213},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.478523850440979},{"id":"https://openalex.org/C2777472644","wikidata":"https://www.wikidata.org/wiki/Q16968992","display_name":"Approximate inference","level":3,"score":0.47736072540283203},{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.47583866119384766},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.4489330053329468},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.42521244287490845},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4211939871311188},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34889814257621765},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3350452780723572},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.2935820519924164},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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":1,"locations":[{"id":"doi:10.1109/isbi.2013.6556560","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2013.6556560","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE 10th International Symposium on Biomedical Imaging","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W117661170","https://openalex.org/W202223315","https://openalex.org/W2109325056","https://openalex.org/W2118056016","https://openalex.org/W2121332494","https://openalex.org/W2123175289","https://openalex.org/W2147828785","https://openalex.org/W2155501738","https://openalex.org/W2160041854","https://openalex.org/W2465041517","https://openalex.org/W2911964244","https://openalex.org/W6604872404","https://openalex.org/W6608198899"],"related_works":["https://openalex.org/W2776613281","https://openalex.org/W2962950510","https://openalex.org/W4226287370","https://openalex.org/W2114556850","https://openalex.org/W2153267847","https://openalex.org/W2159992248","https://openalex.org/W959529772","https://openalex.org/W4240337634","https://openalex.org/W3021913283","https://openalex.org/W2070797946"],"abstract_inverted_index":{"When":[0],"tracking":[1],"and":[2,47,93,100],"segmenting":[3],"multiple":[4],"objects":[5,71],"under":[6],"heavy":[7],"occlusion,":[8],"a":[9,18,32,58],"large":[10],"class":[11],"of":[12,25,44,49,66,70],"algorithms":[13],"can":[14],"greatly":[15],"benefit":[16],"from":[17],"preprocessing":[19],"that":[20,86],"reliably":[21],"assesses":[22],"the":[23,64,68,80],"number":[24,69],"individuals":[26],"in":[27,72],"each":[28,73],"cluster.":[29],"This":[30],"is":[31,94],"difficult":[33],"task":[34],"when":[35],"relying":[36],"on":[37],"local":[38,91],"information":[39],"only,":[40],"due":[41],"to":[42,62,96],"scarcity":[43],"training":[45],"examples":[46],"lack":[48],"strongly":[50],"predictive":[51],"features.":[52],"In":[53],"this":[54],"paper,":[55],"we":[56],"develop":[57],"deterministic":[59],"graphical":[60],"model":[61],"address":[63],"problem":[65],"counting":[67],"foreground":[74],"region":[75],"as":[76],"global":[77,87],"inference":[78,88],"across":[79],"entire":[81],"video":[82],"sequence.":[83],"We":[84],"show":[85],"improves":[89],"over":[90],"predictions,":[92],"able":[95],"produce":[97],"an":[98,104],"accurate":[99],"coherent":[101],"output":[102],"within":[103],"useful":[105],"runtime.":[106]},"counts_by_year":[{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}