{"id":"https://openalex.org/W2767056669","doi":"https://doi.org/10.1109/mits.2017.2743171","title":"Online Recognition of Driver-Activity Based on Visual Scanpath Classification","display_name":"Online Recognition of Driver-Activity Based on Visual Scanpath Classification","publication_year":2017,"publication_date":"2017-01-01","ids":{"openalex":"https://openalex.org/W2767056669","doi":"https://doi.org/10.1109/mits.2017.2743171","mag":"2767056669"},"language":"en","primary_location":{"id":"doi:10.1109/mits.2017.2743171","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mits.2017.2743171","pdf_url":null,"source":{"id":"https://openalex.org/S131000621","display_name":"IEEE Intelligent Transportation Systems Magazine","issn_l":"1939-1390","issn":["1939-1390","1941-1197"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Intelligent Transportation Systems Magazine","raw_type":"journal-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/A5019744304","display_name":"Christian Braunagel","orcid":null},"institutions":[{"id":"https://openalex.org/I891521709","display_name":"Daimler (Germany)","ror":"https://ror.org/00m0j3d84","country_code":"DE","type":"company","lineage":["https://openalex.org/I891521709"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Christian Braunagel","raw_affiliation_strings":["RD/FAV Team \u201cCamera Systems\u201d, Daimler AG, Sindelfingen, Germany","RD/FAV Team \"Camera Systems\", Daimler AG, Sindelfingen, Germany"],"affiliations":[{"raw_affiliation_string":"RD/FAV Team \u201cCamera Systems\u201d, Daimler AG, Sindelfingen, Germany","institution_ids":["https://openalex.org/I891521709"]},{"raw_affiliation_string":"RD/FAV Team \"Camera Systems\", Daimler AG, Sindelfingen, Germany","institution_ids":["https://openalex.org/I891521709"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070979587","display_name":"David Geisler","orcid":null},"institutions":[{"id":"https://openalex.org/I8087733","display_name":"University of T\u00fcbingen","ror":"https://ror.org/03a1kwz48","country_code":"DE","type":"education","lineage":["https://openalex.org/I8087733"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"David Geisler","raw_affiliation_strings":["University of T\u00fcbingen"],"affiliations":[{"raw_affiliation_string":"University of T\u00fcbingen","institution_ids":["https://openalex.org/I8087733"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087076980","display_name":"Wolfgang Rosenstiel","orcid":null},"institutions":[{"id":"https://openalex.org/I8087733","display_name":"University of T\u00fcbingen","ror":"https://ror.org/03a1kwz48","country_code":"DE","type":"education","lineage":["https://openalex.org/I8087733"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Wolfgang Rosenstiel","raw_affiliation_strings":["University of T\u00fcbingen"],"affiliations":[{"raw_affiliation_string":"University of T\u00fcbingen","institution_ids":["https://openalex.org/I8087733"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008809634","display_name":"Enkelejda Kasneci","orcid":"https://orcid.org/0000-0003-3146-4484"},"institutions":[{"id":"https://openalex.org/I8087733","display_name":"University of T\u00fcbingen","ror":"https://ror.org/03a1kwz48","country_code":"DE","type":"education","lineage":["https://openalex.org/I8087733"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Enkelejda Kasneci","raw_affiliation_strings":["University of T\u00fcbingen"],"affiliations":[{"raw_affiliation_string":"University of T\u00fcbingen","institution_ids":["https://openalex.org/I8087733"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5019744304"],"corresponding_institution_ids":["https://openalex.org/I891521709"],"apc_list":null,"apc_paid":null,"fwci":5.5525,"has_fulltext":false,"cited_by_count":43,"citation_normalized_percentile":{"value":0.95750324,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"9","issue":"4","first_page":"23","last_page":"36"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10525","display_name":"Human-Automation Interaction and Safety","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10525","display_name":"Human-Automation Interaction and Safety","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9965000152587891,"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/T11707","display_name":"Gaze Tracking and Assistive Technology","score":0.9789999723434448,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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":0.6765226125717163},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6318075060844421},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5775046348571777},{"id":"https://openalex.org/keywords/automation","display_name":"Automation","score":0.5157292485237122},{"id":"https://openalex.org/keywords/window","display_name":"Window (computing)","score":0.4826301038265228},{"id":"https://openalex.org/keywords/mobile-device","display_name":"Mobile device","score":0.47651445865631104},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45804092288017273},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.44618338346481323},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3863946199417114},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37898439168930054},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35324516892433167},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.19507721066474915}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6765226125717163},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6318075060844421},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5775046348571777},{"id":"https://openalex.org/C115901376","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automation","level":2,"score":0.5157292485237122},{"id":"https://openalex.org/C2778751112","wikidata":"https://www.wikidata.org/wiki/Q835016","display_name":"Window (computing)","level":2,"score":0.4826301038265228},{"id":"https://openalex.org/C186967261","wikidata":"https://www.wikidata.org/wiki/Q5082128","display_name":"Mobile device","level":2,"score":0.47651445865631104},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45804092288017273},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.44618338346481323},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3863946199417114},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37898439168930054},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35324516892433167},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.19507721066474915},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mits.2017.2743171","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mits.2017.2743171","pdf_url":null,"source":{"id":"https://openalex.org/S131000621","display_name":"IEEE Intelligent Transportation Systems Magazine","issn_l":"1939-1390","issn":["1939-1390","1941-1197"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Intelligent Transportation Systems Magazine","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W201421746","https://openalex.org/W1661871015","https://openalex.org/W1945120929","https://openalex.org/W1977965306","https://openalex.org/W2007266026","https://openalex.org/W2015831141","https://openalex.org/W2016711711","https://openalex.org/W2017634428","https://openalex.org/W2050905760","https://openalex.org/W2054780155","https://openalex.org/W2054849844","https://openalex.org/W2059303722","https://openalex.org/W2102804490","https://openalex.org/W2114615169","https://openalex.org/W2117074369","https://openalex.org/W2126698740","https://openalex.org/W2144902422","https://openalex.org/W2152264487","https://openalex.org/W2155268664","https://openalex.org/W2159613676","https://openalex.org/W2164274563","https://openalex.org/W2180794161","https://openalex.org/W2300673152","https://openalex.org/W2340043522","https://openalex.org/W2419295800","https://openalex.org/W2462394972","https://openalex.org/W2466005698","https://openalex.org/W2497909917","https://openalex.org/W4235485727","https://openalex.org/W4247387102","https://openalex.org/W4285719527","https://openalex.org/W6636914306","https://openalex.org/W6681302627","https://openalex.org/W6719070815"],"related_works":["https://openalex.org/W2109115373","https://openalex.org/W2390901981","https://openalex.org/W4230691760","https://openalex.org/W3034529322","https://openalex.org/W2393847170","https://openalex.org/W85049056","https://openalex.org/W158465905","https://openalex.org/W577521963","https://openalex.org/W2054277467","https://openalex.org/W3112082055"],"abstract_inverted_index":{"The":[0,136],"next":[1],"step":[2],"towards":[3],"the":[4,9,15,22,37,41,47,76,86,92,112,126,152,159,171,174,189,198,202],"fully":[5],"automated":[6,16,57],"vehicle":[7],"is":[8,49,96,108,118,194],"level":[10],"of":[11,100,114,128,139,154,161,182,188,201,208,211],"conditional":[12],"automation,":[13],"where":[14],"driving":[17,42,130],"system":[18],"can":[19],"take":[20],"over":[21],"control":[23],"and":[24,103,158,193],"responsibility":[25],"for":[26,68,75,145,205],"a":[27,60,79,121,129,164,178,185,209],"limited":[28],"time":[29,81],"interval.":[30],"Nevertheless,":[31],"take-over":[32,62],"situations":[33],"may":[34],"occur,":[35],"forcing":[36],"driver":[38,48,203],"to":[39,51,120,151,170,196],"resume":[40],"task.":[43],"Despite":[44],"such":[45],"situations,":[46],"able":[50,195],"perform":[52],"secondary":[53,156,199],"tasks":[54,157,200],"during":[55],"conditionally":[56],"driving,":[58],"hence":[59],"low":[61],"quality":[63],"must":[64],"be":[65],"expected.":[66],"Methods":[67],"Driver-Activity":[69],"Recognition":[70],"(DAR)":[71],"usually":[72],"extract":[73],"features":[74],"classification":[77,137,179,191],"within":[78],"moving":[80],"window.":[82],"In":[83],"this":[84,115],"paper,":[85],"first":[87],"DAR":[88,141],"architecture":[89],"based":[90,124],"on":[91,125],"driver's":[93],"scanpath,":[94],"which":[95],"extracted":[97],"by":[98],"means":[99],"dynamic":[101],"clustering":[102],"symbolic":[104],"aggregate":[105],"approximation":[106],"patterns,":[107],"introduced.":[109],"To":[110],"demonstrate":[111],"potential":[113],"approach,":[116,173],"it":[117],"compared":[119],"state-of-the-art":[122,172],"method":[123,176],"data":[127],"simulator":[131],"study":[132],"with":[133,149,215],"82":[134],"subjects.":[135],"performance":[138],"both":[140],"approaches":[142],"was":[143],"examined":[144],"decreasing":[146],"window":[147],"sizes":[148],"regard":[150],"recognition":[153],"different":[155],"separability":[160],"drivers":[162],"using":[163],"handheld":[165],"or":[166],"hands-free":[167],"device.":[168],"Compared":[169],"proposed":[175],"shows":[177],"accuracy":[180],"increase":[181],"nearly":[183],"20%,":[184],"significant":[186],"improvement":[187],"overall":[190],"performance,":[192],"classify":[197],"even":[204],"short":[206],"windows":[207],"duration":[210],"5":[212],"s,":[213],"i.e.":[214],"little":[216],"information.":[217]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":1}],"updated_date":"2026-03-26T15:22:09.906841","created_date":"2025-10-10T00:00:00"}
