{"id":"https://openalex.org/W2793083264","doi":"https://doi.org/10.1109/itsc.2017.8317922","title":"Learning temporal features with CNNs for monocular visual ego motion estimation","display_name":"Learning temporal features with CNNs for monocular visual ego motion estimation","publication_year":2017,"publication_date":"2017-10-01","ids":{"openalex":"https://openalex.org/W2793083264","doi":"https://doi.org/10.1109/itsc.2017.8317922","mag":"2793083264"},"language":"en","primary_location":{"id":"doi:10.1109/itsc.2017.8317922","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2017.8317922","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC)","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/A5103159140","display_name":"Michael Weber","orcid":"https://orcid.org/0000-0002-2692-5568"},"institutions":[{"id":"https://openalex.org/I143379178","display_name":"FZI Research Center for Information Technology","ror":"https://ror.org/04kdh6x72","country_code":"DE","type":"nonprofit","lineage":["https://openalex.org/I143379178"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Michael Weber","raw_affiliation_strings":["FZI Research Center for Information Technology, Karlsruhe, Germany"],"affiliations":[{"raw_affiliation_string":"FZI Research Center for Information Technology, Karlsruhe, Germany","institution_ids":["https://openalex.org/I143379178"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033180385","display_name":"Christoph Rist","orcid":null},"institutions":[{"id":"https://openalex.org/I143379178","display_name":"FZI Research Center for Information Technology","ror":"https://ror.org/04kdh6x72","country_code":"DE","type":"nonprofit","lineage":["https://openalex.org/I143379178"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Christoph Rist","raw_affiliation_strings":["FZI Research Center for Information Technology, Karlsruhe, Germany"],"affiliations":[{"raw_affiliation_string":"FZI Research Center for Information Technology, Karlsruhe, Germany","institution_ids":["https://openalex.org/I143379178"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060028048","display_name":"J. Marius Z\u00f6llner","orcid":"https://orcid.org/0000-0001-6190-7202"},"institutions":[{"id":"https://openalex.org/I143379178","display_name":"FZI Research Center for Information Technology","ror":"https://ror.org/04kdh6x72","country_code":"DE","type":"nonprofit","lineage":["https://openalex.org/I143379178"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"J. Marius Zollner","raw_affiliation_strings":["FZI Research Center for Information Technology, Karlsruhe, Germany"],"affiliations":[{"raw_affiliation_string":"FZI Research Center for Information Technology, Karlsruhe, Germany","institution_ids":["https://openalex.org/I143379178"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5103159140"],"corresponding_institution_ids":["https://openalex.org/I143379178"],"apc_list":null,"apc_paid":null,"fwci":0.5461,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.77006734,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9993000030517578,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9993000030517578,"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":0.9976999759674072,"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":0.9736999869346619,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/monocular","display_name":"Monocular","score":0.7811756134033203},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7705368995666504},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6906320452690125},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6304869651794434},{"id":"https://openalex.org/keywords/motion-estimation","display_name":"Motion estimation","score":0.5683605670928955},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.5588003396987915},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.43786293268203735},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40202683210372925}],"concepts":[{"id":"https://openalex.org/C65909025","wikidata":"https://www.wikidata.org/wiki/Q1945033","display_name":"Monocular","level":2,"score":0.7811756134033203},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7705368995666504},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6906320452690125},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6304869651794434},{"id":"https://openalex.org/C10161872","wikidata":"https://www.wikidata.org/wiki/Q557891","display_name":"Motion estimation","level":2,"score":0.5683605670928955},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.5588003396987915},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.43786293268203735},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40202683210372925}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itsc.2017.8317922","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2017.8317922","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC)","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":32,"referenced_works":["https://openalex.org/W1520997877","https://openalex.org/W1522301498","https://openalex.org/W1533861849","https://openalex.org/W1585377561","https://openalex.org/W1910657905","https://openalex.org/W1936750108","https://openalex.org/W1983364832","https://openalex.org/W2016053056","https://openalex.org/W2115579991","https://openalex.org/W2150066425","https://openalex.org/W2157364932","https://openalex.org/W2168676389","https://openalex.org/W2200124539","https://openalex.org/W2220063164","https://openalex.org/W2400202024","https://openalex.org/W2512944926","https://openalex.org/W2530906228","https://openalex.org/W2555820268","https://openalex.org/W2562137921","https://openalex.org/W2592936284","https://openalex.org/W2612774882","https://openalex.org/W2963881378","https://openalex.org/W2964121744","https://openalex.org/W4297666078","https://openalex.org/W4297780676","https://openalex.org/W4299978048","https://openalex.org/W6631190155","https://openalex.org/W6631943919","https://openalex.org/W6635292102","https://openalex.org/W6639780620","https://openalex.org/W6730099391","https://openalex.org/W6730565506"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W200819717","https://openalex.org/W2032269556","https://openalex.org/W1991834176","https://openalex.org/W2944448661","https://openalex.org/W2064421702","https://openalex.org/W4253756925","https://openalex.org/W2805523177","https://openalex.org/W4321487865","https://openalex.org/W2131956013"],"abstract_inverted_index":{"Making":[0],"Convolutional":[1],"Neural":[2],"Networks":[3],"(CNNs)":[4],"successful":[5],"in":[6,77,105],"learning":[7],"problems":[8,66],"like":[9,67,107],"image":[10],"based":[11],"ego":[12,68,78],"motion":[13,69,79],"estimation,":[14],"highly":[15],"depends":[16],"on":[17],"the":[18,21,25,31,37,55,94],"ability":[19],"of":[20,33,57],"network":[22,35],"to":[23,39,51,64],"extract":[24],"temporal":[26,41,59,91],"information":[27,60],"from":[28],"videos.":[29],"Therefore,":[30],"architecture":[32],"a":[34,84],"needs":[36],"capability":[38],"learn":[40,52],"features.":[42],"We":[43],"propose":[44],"two":[45],"CNN":[46],"architectures":[47,72,95],"which":[48],"are":[49,62],"able":[50,63],"features":[53],"for":[54,87],"extraction":[56],"this":[58],"and":[61,81],"solve":[65],"estimation.":[70],"Our":[71],"achieve":[73],"first":[74],"promising":[75],"results":[76],"estimation":[80],"might":[82],"be":[83,103],"good":[85],"foundation":[86],"systems":[88],"dealing":[89],"with":[90],"information.":[92],"As":[93],"reach":[96],"real":[97],"time":[98],"inference":[99],"time,":[100],"they":[101],"can":[102],"applied":[104],"domains":[106],"autonomous":[108],"driving.":[109]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
