{"id":"https://openalex.org/W2963065506","doi":"https://doi.org/10.1109/ssci.2017.8285238","title":"Robust tracking and behavioral modeling of movements of biological collectives from ordinary video recordings","display_name":"Robust tracking and behavioral modeling of movements of biological collectives from ordinary video recordings","publication_year":2017,"publication_date":"2017-11-01","ids":{"openalex":"https://openalex.org/W2963065506","doi":"https://doi.org/10.1109/ssci.2017.8285238","mag":"2963065506"},"language":"en","primary_location":{"id":"doi:10.1109/ssci.2017.8285238","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssci.2017.8285238","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE Symposium Series on Computational Intelligence (SSCI)","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/A5052717630","display_name":"Hiroki Sayama","orcid":"https://orcid.org/0000-0002-2670-5864"},"institutions":[{"id":"https://openalex.org/I123946342","display_name":"Binghamton University","ror":"https://ror.org/008rmbt77","country_code":"US","type":"education","lineage":["https://openalex.org/I123946342"]},{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP","US"],"is_corresponding":false,"raw_author_name":"Hiroki Sayama","raw_affiliation_strings":["Department of Systems Science and Industrial Engineering Binghamton University, State University of New York, New York, Binghamton","Faculty of Commerce, Waseda University, Shiniuku, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Systems Science and Industrial Engineering Binghamton University, State University of New York, New York, Binghamton","institution_ids":["https://openalex.org/I123946342"]},{"raw_affiliation_string":"Faculty of Commerce, Waseda University, Shiniuku, Tokyo, Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075493826","display_name":"Farnaz Zamani Esfahlani","orcid":"https://orcid.org/0000-0001-9539-4919"},"institutions":[{"id":"https://openalex.org/I123946342","display_name":"Binghamton University","ror":"https://ror.org/008rmbt77","country_code":"US","type":"education","lineage":["https://openalex.org/I123946342"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Farnaz Zamani Esfahlani","raw_affiliation_strings":["Department of Systems Science and Industrial Engineering Binghamton University, State University of New York, New York, Binghamton"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Systems Science and Industrial Engineering Binghamton University, State University of New York, New York, Binghamton","institution_ids":["https://openalex.org/I123946342"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015456283","display_name":"Ali Jazayeri","orcid":"https://orcid.org/0000-0002-6468-1971"},"institutions":[{"id":"https://openalex.org/I72816309","display_name":"Drexel University","ror":"https://ror.org/04bdffz58","country_code":"US","type":"education","lineage":["https://openalex.org/I72816309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ali Jazayeri","raw_affiliation_strings":["Drexel University, Philadelphia, PA, US"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Drexel University, Philadelphia, PA, US","institution_ids":["https://openalex.org/I72816309"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090264814","display_name":"J. Scott Turner","orcid":"https://orcid.org/0000-0003-2457-6138"},"institutions":[{"id":"https://openalex.org/I103497121","display_name":"Purchase College","ror":"https://ror.org/057trrr89","country_code":"US","type":"education","lineage":["https://openalex.org/I103497121"]},{"id":"https://openalex.org/I157349981","display_name":"SUNY College of Environmental Science and Forestry","ror":"https://ror.org/00qv0tw17","country_code":"US","type":"education","lineage":["https://openalex.org/I157349981"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"J. Scott Turner","raw_affiliation_strings":["Department of Biology, SUNY College of Environmental Science and Forestry, Forestry, Syracuse, NY"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biology, SUNY College of Environmental Science and Forestry, Forestry, Syracuse, NY","institution_ids":["https://openalex.org/I103497121","https://openalex.org/I157349981"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.34560015,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11500","display_name":"Evacuation and Crowd Dynamics","score":0.995199978351593,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11500","display_name":"Evacuation and Crowd Dynamics","score":0.995199978351593,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11252","display_name":"Evolutionary Game Theory and Cooperation","score":0.9782999753952026,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10702","display_name":"Insect and Arachnid Ecology and Behavior","score":0.9729999899864197,"subfield":{"id":"https://openalex.org/subfields/1311","display_name":"Genetics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.742779016494751},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.6370319128036499},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.628328800201416},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5288264155387878},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.4646183252334595},{"id":"https://openalex.org/keywords/finite-state-machine","display_name":"Finite-state machine","score":0.4518640637397766},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.4453933835029602},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4274459779262543},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.3711816072463989},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36436885595321655},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.32716071605682373},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.15287989377975464},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.14393556118011475},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.13591426610946655},{"id":"https://openalex.org/keywords/video-processing","display_name":"Video processing","score":0.08405527472496033}],"concepts":[{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.742779016494751},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.6370319128036499},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.628328800201416},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5288264155387878},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.4646183252334595},{"id":"https://openalex.org/C167822520","wikidata":"https://www.wikidata.org/wiki/Q176452","display_name":"Finite-state machine","level":2,"score":0.4518640637397766},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.4453933835029602},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4274459779262543},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3711816072463989},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36436885595321655},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.32716071605682373},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.15287989377975464},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.14393556118011475},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13591426610946655},{"id":"https://openalex.org/C65483669","wikidata":"https://www.wikidata.org/wiki/Q3536669","display_name":"Video processing","level":2,"score":0.08405527472496033},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ssci.2017.8285238","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssci.2017.8285238","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE Symposium Series on Computational Intelligence (SSCI)","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":10,"referenced_works":["https://openalex.org/W1977591411","https://openalex.org/W1999242419","https://openalex.org/W2001457444","https://openalex.org/W2087262824","https://openalex.org/W2098981639","https://openalex.org/W2110935965","https://openalex.org/W2117342758","https://openalex.org/W2913808704","https://openalex.org/W2962979505","https://openalex.org/W3157685993"],"related_works":["https://openalex.org/W2392100589","https://openalex.org/W4285271403","https://openalex.org/W2542007731","https://openalex.org/W2968379562","https://openalex.org/W2091015105","https://openalex.org/W4388689193","https://openalex.org/W2110899030","https://openalex.org/W29633852","https://openalex.org/W2985362983","https://openalex.org/W4327670844"],"abstract_inverted_index":{"We":[0,66],"propose":[1],"a":[2,18,47,88,94],"novel":[3],"computational":[4],"method":[5,35,71],"to":[6,74],"extract":[7],"information":[8],"about":[9],"interactions":[10,119],"among":[11],"individuals":[12,27,43,62,124],"with":[13,125],"different":[14,126],"behavioral":[15,39],"states":[16,40,59],"in":[17,63,80,87],"biological":[19,77],"collective":[20],"from":[21],"ordinary":[22],"video":[23],"recordings.":[24],"Assuming":[25],"that":[26],"are":[28],"acting":[29],"as":[30],"finite":[31],"state":[32,51],"machines,":[33],"our":[34],"first":[36],"detects":[37],"discrete":[38],"of":[41,49,60,131],"those":[42],"and":[44,58,84],"then":[45],"constructs":[46],"model":[48],"their":[50],"transitions,":[52],"taking":[53],"into":[54],"account":[55],"the":[56,64,69,129,132],"positions":[57],"other":[61],"vicinity.":[65],"have":[67],"tested":[68],"proposed":[70,133],"through":[72],"applications":[73],"two":[75],"real-world":[76],"collectives:":[78],"termites":[79],"an":[81],"experimental":[82],"setting":[83],"human":[85,103],"pedestrians":[86],"university":[89],"campus.":[90],"For":[91],"each":[92],"application,":[93],"robust":[95],"tracking":[96],"system":[97],"was":[98],"developed":[99],"in-house,":[100],"utilizing":[101],"interactive":[102],"intervention":[104],"(for":[105,112],"termite":[106],"tracking)":[107],"or":[108],"online":[109],"agent-based":[110],"simulation":[111],"pedestrian":[113],"tracking).":[114],"In":[115],"both":[116],"cases,":[117],"significant":[118],"were":[120],"detected":[121],"between":[122],"nearby":[123],"states,":[127],"demonstrating":[128],"effectiveness":[130],"method.":[134]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
