{"id":"https://openalex.org/W2096473039","doi":"https://doi.org/10.1109/ivs.2011.5940516","title":"Efficient monocular vehicle orientation estimation using a tree-based classifier","display_name":"Efficient monocular vehicle orientation estimation using a tree-based classifier","publication_year":2011,"publication_date":"2011-06-01","ids":{"openalex":"https://openalex.org/W2096473039","doi":"https://doi.org/10.1109/ivs.2011.5940516","mag":"2096473039"},"language":"en","primary_location":{"id":"doi:10.1109/ivs.2011.5940516","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2011.5940516","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE Intelligent Vehicles Symposium (IV)","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/A5013575926","display_name":"Michael Gabb","orcid":null},"institutions":[{"id":"https://openalex.org/I196349391","display_name":"Universit\u00e4t Ulm","ror":"https://ror.org/032000t02","country_code":"DE","type":"education","lineage":["https://openalex.org/I196349391"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Michael Gabb","raw_affiliation_strings":["Department of Measurement, Control and Microtechnology, University of Ulm (EBS), Ulm, Germany","University of Ulm, Dept. of Measurement, Control and Microtechnology, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Measurement, Control and Microtechnology, University of Ulm (EBS), Ulm, Germany","institution_ids":["https://openalex.org/I196349391"]},{"raw_affiliation_string":"University of Ulm, Dept. of Measurement, Control and Microtechnology, Germany","institution_ids":["https://openalex.org/I196349391"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065500684","display_name":"Otto L\u00f6hlein","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":false,"raw_author_name":"Otto Lohlein","raw_affiliation_strings":["Department GR/PAP, Daimler Benz Aerospace, Ulm, Germany","[Daimler AG, Dept. GR/PAP, Ulm, Germany]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department GR/PAP, Daimler Benz Aerospace, Ulm, Germany","institution_ids":["https://openalex.org/I891521709"]},{"raw_affiliation_string":"[Daimler AG, Dept. GR/PAP, Ulm, Germany]","institution_ids":["https://openalex.org/I891521709"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068613595","display_name":"Matthias Oberl\u00e4nder","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":false,"raw_author_name":"Matthias Oberlander","raw_affiliation_strings":["Department GR/PAP, Daimler Benz Aerospace, Ulm, Germany","[Daimler AG, Dept. GR/PAP, Ulm, Germany]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department GR/PAP, Daimler Benz Aerospace, Ulm, Germany","institution_ids":["https://openalex.org/I891521709"]},{"raw_affiliation_string":"[Daimler AG, Dept. GR/PAP, Ulm, Germany]","institution_ids":["https://openalex.org/I891521709"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036545001","display_name":"Gunther Heidemann","orcid":null},"institutions":[{"id":"https://openalex.org/I100066346","display_name":"University of Stuttgart","ror":"https://ror.org/04vnq7t77","country_code":"DE","type":"education","lineage":["https://openalex.org/I100066346"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Gunther Heidemann","raw_affiliation_strings":["Intelligent Systems Group, University of Stuttgart, Stuttgart, Germany","[University of Stuttgart, Intelligent Systems Group, Germany]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Intelligent Systems Group, University of Stuttgart, Stuttgart, Germany","institution_ids":["https://openalex.org/I100066346"]},{"raw_affiliation_string":"[University of Stuttgart, Intelligent Systems Group, Germany]","institution_ids":["https://openalex.org/I100066346"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.0935,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.89487793,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"308","last_page":"313"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9995999932289124,"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":0.9995999932289124,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T10036","display_name":"Advanced Neural Network Applications","score":0.998199999332428,"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/classifier","display_name":"Classifier (UML)","score":0.7620908617973328},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7030535340309143},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6705659031867981},{"id":"https://openalex.org/keywords/monocular","display_name":"Monocular","score":0.6304140686988831},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5293142199516296},{"id":"https://openalex.org/keywords/monocular-vision","display_name":"Monocular vision","score":0.5262207984924316},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.4758871793746948},{"id":"https://openalex.org/keywords/automotive-industry","display_name":"Automotive industry","score":0.4675869941711426},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4486808180809021},{"id":"https://openalex.org/keywords/tree-structure","display_name":"Tree structure","score":0.425637423992157},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.21082550287246704},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1632668673992157}],"concepts":[{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.7620908617973328},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7030535340309143},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6705659031867981},{"id":"https://openalex.org/C65909025","wikidata":"https://www.wikidata.org/wiki/Q1945033","display_name":"Monocular","level":2,"score":0.6304140686988831},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5293142199516296},{"id":"https://openalex.org/C158829959","wikidata":"https://www.wikidata.org/wiki/Q1640606","display_name":"Monocular vision","level":2,"score":0.5262207984924316},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.4758871793746948},{"id":"https://openalex.org/C526921623","wikidata":"https://www.wikidata.org/wiki/Q190117","display_name":"Automotive industry","level":2,"score":0.4675869941711426},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4486808180809021},{"id":"https://openalex.org/C163797641","wikidata":"https://www.wikidata.org/wiki/Q2067937","display_name":"Tree structure","level":3,"score":0.425637423992157},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.21082550287246704},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1632668673992157},{"id":"https://openalex.org/C197855036","wikidata":"https://www.wikidata.org/wiki/Q380172","display_name":"Binary tree","level":2,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ivs.2011.5940516","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2011.5940516","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE Intelligent Vehicles Symposium (IV)","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":23,"referenced_works":["https://openalex.org/W1589135814","https://openalex.org/W1952052958","https://openalex.org/W2032210760","https://openalex.org/W2114687015","https://openalex.org/W2116510335","https://openalex.org/W2117203466","https://openalex.org/W2120907774","https://openalex.org/W2135292614","https://openalex.org/W2143071398","https://openalex.org/W2146036766","https://openalex.org/W2149077040","https://openalex.org/W2149197198","https://openalex.org/W2169696215","https://openalex.org/W2739698496","https://openalex.org/W3097096317","https://openalex.org/W3110683067","https://openalex.org/W3214102110","https://openalex.org/W4244952642","https://openalex.org/W6677221034","https://openalex.org/W6677540724","https://openalex.org/W6741565869","https://openalex.org/W6786768871","https://openalex.org/W6804270185"],"related_works":["https://openalex.org/W3213997683","https://openalex.org/W2995270189","https://openalex.org/W2084124712","https://openalex.org/W2435467664","https://openalex.org/W2091635186","https://openalex.org/W4381188157","https://openalex.org/W2011626633","https://openalex.org/W2037866696","https://openalex.org/W4251947321","https://openalex.org/W2027891072"],"abstract_inverted_index":{"For":[0],"automotive":[1],"assistance":[2],"systems,":[3],"on-road":[4],"vehicle":[5,39,79],"detection":[6],"is":[7,44,64,138,158],"a":[8,20,51,87,132,162,167],"key":[9],"challenge":[10],"to":[11,36,76,107,122,155,173],"forward":[12],"collision":[13],"warning.":[14],"Along":[15],"with":[16],"detecting":[17],"existence,":[18],"determining":[19],"vehicle's":[21,72],"orientation":[22],"plays":[23],"an":[24,34],"important":[25],"role":[26],"in":[27],"correctly":[28],"predicting":[29],"maneuvers.":[30],"In":[31],"this":[32],"paper,":[33],"approach":[35],"remotely":[37],"estimate":[38],"orientations":[40],"from":[41],"monocular":[42],"images":[43],"presented.":[45],"The":[46],"proposed":[47,183],"system":[48],"operates":[49],"on":[50,93],"per":[52],"frame":[53],"basis":[54],"and":[55,99,179],"does":[56],"not":[57],"require":[58,118],"any":[59],"depth":[60],"cues.":[61],"Orientation":[62],"estimation":[63],"performed":[65],"by":[66,97,161],"analyzing":[67],"the":[68,71,77,94,101,108,112,129,141,150,177,182],"position":[69,82],"of":[70,152,181],"rear":[73],"section":[74],"relative":[75],"overall":[78,113],"outline.":[80],"Both":[81],"types":[83],"are":[84],"determined":[85],"using":[86,140],"newly":[88],"devised":[89],"tree-structured":[90],"classifier.":[91],"Based":[92],"cascaded":[95],"structure":[96],"Viola":[98],"Jones,":[100],"pro":[102],"posed":[103],"classifier":[104,168],"adapts":[105],"itself":[106],"problem's":[109],"structure,":[110],"dividing":[111],"problem":[114],"into":[115],"parts":[116],"that":[117,127,169],"fewer":[119],"weak":[120],"learners":[121],"solve.":[123],"To":[124,145],"find":[125],"partitions":[126],"simplify":[128],"classification":[130],"task,":[131],"quality":[133],"criterion":[134],"measuring":[135],"class":[136],"separability":[137],"optimized":[139],"Simulated":[142],"Annealing":[143],"algorithm.":[144],"further":[146],"increase":[147],"processing":[148],"speed,":[149],"number":[151],"tree":[153],"nodes":[154],"be":[156],"traversed":[157],"drastically":[159],"reduced":[160],"two-staged":[163],"boosting":[164],"procedure,":[165],"training":[166],"decides":[170],"which":[171],"branch":[172],"take.":[174],"Experiments":[175],"show":[176],"relevance":[178],"effectiveness":[180],"concepts.":[184]},"counts_by_year":[{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":3},{"year":2013,"cited_by_count":5},{"year":2012,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
