{"id":"https://openalex.org/W3160404002","doi":"https://doi.org/10.1109/icpr48806.2021.9413233","title":"Image Sequence Based Cyclist Action Recognition Using Multi-Stream 3D Convolution","display_name":"Image Sequence Based Cyclist Action Recognition Using Multi-Stream 3D Convolution","publication_year":2021,"publication_date":"2021-01-10","ids":{"openalex":"https://openalex.org/W3160404002","doi":"https://doi.org/10.1109/icpr48806.2021.9413233","mag":"3160404002"},"language":"en","primary_location":{"id":"doi:10.1109/icpr48806.2021.9413233","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9413233","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","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/A5086864323","display_name":"Stefan Zernetsch","orcid":"https://orcid.org/0000-0003-2016-5059"},"institutions":[{"id":"https://openalex.org/I4210158205","display_name":"Aschaffenburg University of Applied Sciences","ror":"https://ror.org/04sms9203","country_code":"DE","type":"education","lineage":["https://openalex.org/I4210158205"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Stefan Zernetsch","raw_affiliation_strings":["University of Applied Sciences Aschaffenburg Aschaffenburg, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Applied Sciences Aschaffenburg Aschaffenburg, Germany","institution_ids":["https://openalex.org/I4210158205"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020906877","display_name":"Steven Schreck","orcid":null},"institutions":[{"id":"https://openalex.org/I4210158205","display_name":"Aschaffenburg University of Applied Sciences","ror":"https://ror.org/04sms9203","country_code":"DE","type":"education","lineage":["https://openalex.org/I4210158205"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Steven Schreck","raw_affiliation_strings":["University of Applied Sciences Aschaffenburg Aschaffenburg, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Applied Sciences Aschaffenburg Aschaffenburg, Germany","institution_ids":["https://openalex.org/I4210158205"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016665121","display_name":"Viktor Kre\u00df","orcid":"https://orcid.org/0000-0002-9314-2424"},"institutions":[{"id":"https://openalex.org/I4210158205","display_name":"Aschaffenburg University of Applied Sciences","ror":"https://ror.org/04sms9203","country_code":"DE","type":"education","lineage":["https://openalex.org/I4210158205"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Viktor Kress","raw_affiliation_strings":["University of Applied Sciences Aschaffenburg Aschaffenburg, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Applied Sciences Aschaffenburg Aschaffenburg, Germany","institution_ids":["https://openalex.org/I4210158205"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047844917","display_name":"Konrad Doll","orcid":"https://orcid.org/0000-0002-3746-2319"},"institutions":[{"id":"https://openalex.org/I4210158205","display_name":"Aschaffenburg University of Applied Sciences","ror":"https://ror.org/04sms9203","country_code":"DE","type":"education","lineage":["https://openalex.org/I4210158205"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Konrad Doll","raw_affiliation_strings":["University of Applied Sciences Aschaffenburg Aschaffenburg, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Applied Sciences Aschaffenburg Aschaffenburg, Germany","institution_ids":["https://openalex.org/I4210158205"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065340030","display_name":"Bernhard Sick","orcid":"https://orcid.org/0000-0001-9467-656X"},"institutions":[{"id":"https://openalex.org/I106157433","display_name":"University of Kassel","ror":"https://ror.org/04zc7p361","country_code":"DE","type":"education","lineage":["https://openalex.org/I106157433"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Bernhard Sick","raw_affiliation_strings":["University of Kassel Kassel, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Kassel Kassel, Germany","institution_ids":["https://openalex.org/I106157433"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4851,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.64069934,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"2620","last_page":"2626"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9998999834060669,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9998999834060669,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9994999766349792,"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":0.9976000189781189,"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":0.7742969989776611},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7021182775497437},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.6633670330047607},{"id":"https://openalex.org/keywords/intersection","display_name":"Intersection (aeronautics)","score":0.6633512377738953},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6596488952636719},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5704808831214905},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.5675455331802368},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.5447514653205872},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.5203527808189392},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.5041028261184692},{"id":"https://openalex.org/keywords/movement","display_name":"Movement (music)","score":0.49571096897125244},{"id":"https://openalex.org/keywords/optical-flow","display_name":"Optical flow","score":0.4750932455062866},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.46576619148254395},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37767738103866577},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.34883663058280945},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.09708917140960693}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7742969989776611},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7021182775497437},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6633670330047607},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.6633512377738953},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6596488952636719},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5704808831214905},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.5675455331802368},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.5447514653205872},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.5203527808189392},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.5041028261184692},{"id":"https://openalex.org/C2780226923","wikidata":"https://www.wikidata.org/wiki/Q929848","display_name":"Movement (music)","level":2,"score":0.49571096897125244},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.4750932455062866},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.46576619148254395},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37767738103866577},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.34883663058280945},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.09708917140960693},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","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/C107038049","wikidata":"https://www.wikidata.org/wiki/Q35986","display_name":"Aesthetics","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/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"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/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr48806.2021.9413233","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9413233","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.699999988079071,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W24089286","https://openalex.org/W1861492603","https://openalex.org/W1923404803","https://openalex.org/W1954601274","https://openalex.org/W1970490026","https://openalex.org/W1983364832","https://openalex.org/W2004641798","https://openalex.org/W2031638733","https://openalex.org/W2097117768","https://openalex.org/W2156303437","https://openalex.org/W2197015301","https://openalex.org/W2342662179","https://openalex.org/W2508429489","https://openalex.org/W2557728737","https://openalex.org/W2619947201","https://openalex.org/W2790825277","https://openalex.org/W2793807616","https://openalex.org/W2807456624","https://openalex.org/W2962783540","https://openalex.org/W2963524571","https://openalex.org/W2963782415","https://openalex.org/W2963935518","https://openalex.org/W2990699998","https://openalex.org/W3100457425","https://openalex.org/W4393520377","https://openalex.org/W6600983433","https://openalex.org/W6682864246","https://openalex.org/W6730028961","https://openalex.org/W6955071965"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W2348909947","https://openalex.org/W4292672442","https://openalex.org/W2362101859","https://openalex.org/W2791431590","https://openalex.org/W1978900583","https://openalex.org/W2350688482","https://openalex.org/W2964954556","https://openalex.org/W2762689969","https://openalex.org/W3019910406"],"abstract_inverted_index":{"In":[0],"this":[1],"article,":[2],"we":[3,50],"present":[4],"an":[5,120],"approach":[6,102,121,153,158],"to":[7,112,119],"detect":[8],"basic":[9,98,142,148],"movements":[10],"of":[11,41,71,97,141,147,172],"cyclists":[12,42],"in":[13,78,83],"real":[14,79],"world":[15,80],"traffic":[16,45],"situations":[17],"based":[18,123,157],"on":[19,124],"image":[20],"sequences,":[21,25],"optical":[22],"flow":[23],"(OF)":[24],"and":[26,108,136,144,170],"past":[27],"positions":[28],"using":[29],"a":[30,52,60,67,94],"multi-stream":[31],"3D":[32],"convolutional":[33],"neural":[34],"network":[35],"(3D-ConvNet)":[36],"architecture.":[37],"To":[38],"resolve":[39],"occlusions":[40],"by":[43,93,159],"other":[44],"participants":[46],"or":[47],"road":[48],"structures,":[49],"use":[51],"wide":[53],"angle":[54],"stereo":[55],"camera":[56],"system":[57],"mounted":[58],"at":[59],"heavily":[61],"frequented":[62],"public":[63],"intersection.":[64],"We":[65,115],"created":[66],"large":[68],"dataset":[69,174],"consisting":[70],"1,639":[72],"video":[73],"sequences":[74],"containing":[75],"cyclists,":[76],"recorded":[77],"traffic,":[81],"resulting":[82],"over":[84],"1.1":[85],"million":[86],"samples.":[87],"Through":[88],"modeling":[89],"the":[90,155],"cyclists'":[91],"behavior":[92],"state":[95],"machine":[96],"cyclist":[99],"movements,":[100,143],"our":[101,117,152,173],"takes":[103],"every":[104],"situation":[105],"into":[106,132],"account":[107,133],"is":[109],"not":[110],"limited":[111],"certain":[113],"scenarios.":[114],"compare":[116],"method":[118],"solely":[122],"position":[125,156],"sequences.":[126],"Both":[127],"methods":[128],"are":[129,175],"evaluated":[130],"taking":[131],"frame":[134],"wise":[135,138],"scene":[137],"classification":[139],"results":[140],"detection":[145,166],"times":[146],"movement":[149],"transitions,":[150],"where":[151],"outperforms":[154],"producing":[160],"more":[161],"reliable":[162],"detections":[163],"with":[164],"shorter":[165],"times.":[167],"Our":[168],"code":[169],"parts":[171],"made":[176],"publicly":[177],"available.":[178]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}