{"id":"https://openalex.org/W2087390872","doi":"https://doi.org/10.1109/itsc.2011.6083016","title":"On feature templates for Particle Filter based lane detection","display_name":"On feature templates for Particle Filter based lane detection","publication_year":2011,"publication_date":"2011-10-01","ids":{"openalex":"https://openalex.org/W2087390872","doi":"https://doi.org/10.1109/itsc.2011.6083016","mag":"2087390872"},"language":"en","primary_location":{"id":"doi:10.1109/itsc.2011.6083016","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2011.6083016","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 14th International IEEE 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/A5023054248","display_name":"A. Linarth","orcid":null},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Andre Linarth","raw_affiliation_strings":["Informatics Department, Friedrich Alexander University Erlangen-Nuremberg","Pattern Recognition Lab, Informatics Department, Friedrich Alexander University Erlangen-Nuremberg"],"affiliations":[{"raw_affiliation_string":"Informatics Department, Friedrich Alexander University Erlangen-Nuremberg","institution_ids":["https://openalex.org/I181369854"]},{"raw_affiliation_string":"Pattern Recognition Lab, Informatics Department, Friedrich Alexander University Erlangen-Nuremberg","institution_ids":["https://openalex.org/I181369854"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049805682","display_name":"Elli Angelopoulou","orcid":null},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Elli Angelopoulou","raw_affiliation_strings":["Informatics Department, Friedrich Alexander University Erlangen-Nuremberg","Pattern Recognition Lab, Informatics Department, Friedrich Alexander University Erlangen-Nuremberg"],"affiliations":[{"raw_affiliation_string":"Informatics Department, Friedrich Alexander University Erlangen-Nuremberg","institution_ids":["https://openalex.org/I181369854"]},{"raw_affiliation_string":"Pattern Recognition Lab, Informatics Department, Friedrich Alexander University Erlangen-Nuremberg","institution_ids":["https://openalex.org/I181369854"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5023054248"],"corresponding_institution_ids":["https://openalex.org/I181369854"],"apc_list":null,"apc_paid":null,"fwci":3.5561,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.92792315,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1721","last_page":"1726"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9990000128746033,"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"}},"topics":[{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9990000128746033,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9987999796867371,"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"}},{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9984999895095825,"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/histogram","display_name":"Histogram","score":0.74931800365448},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7446925640106201},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6897833347320557},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6835828423500061},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6632423996925354},{"id":"https://openalex.org/keywords/particle-filter","display_name":"Particle filter","score":0.6552714109420776},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6026799082756042},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.5867774486541748},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5428822040557861},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.48143690824508667},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4368925392627716},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.4261518120765686},{"id":"https://openalex.org/keywords/template","display_name":"Template","score":0.419864684343338},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.39026138186454773},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.229346364736557},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.06833967566490173}],"concepts":[{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.74931800365448},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7446925640106201},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6897833347320557},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6835828423500061},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6632423996925354},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.6552714109420776},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6026799082756042},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.5867774486541748},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5428822040557861},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.48143690824508667},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4368925392627716},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.4261518120765686},{"id":"https://openalex.org/C82714645","wikidata":"https://www.wikidata.org/wiki/Q438331","display_name":"Template","level":2,"score":0.419864684343338},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.39026138186454773},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.229346364736557},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.06833967566490173},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/itsc.2011.6083016","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2011.6083016","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.431.4510","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.431.4510","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www5.informatik.uni-erlangen.de/Forschung/Publikationen/2011/Linarth11-OFT.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.6399999856948853,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1965406246","https://openalex.org/W1991742456","https://openalex.org/W1998771994","https://openalex.org/W2055936398","https://openalex.org/W2067191022","https://openalex.org/W2080553371","https://openalex.org/W2109618991","https://openalex.org/W2109702122","https://openalex.org/W2117658559","https://openalex.org/W2131076267","https://openalex.org/W2143977549","https://openalex.org/W2146575011","https://openalex.org/W2156128637","https://openalex.org/W2159163626","https://openalex.org/W2160337655","https://openalex.org/W2161406034","https://openalex.org/W2161969291","https://openalex.org/W6676579546"],"related_works":["https://openalex.org/W2121300814","https://openalex.org/W4234406076","https://openalex.org/W1886613375","https://openalex.org/W4236081792","https://openalex.org/W4250583430","https://openalex.org/W2010731026","https://openalex.org/W4311328601","https://openalex.org/W2360893094","https://openalex.org/W4390787808","https://openalex.org/W4236036386"],"abstract_inverted_index":{"In":[0],"this":[1,101],"work":[2],"we":[3,42],"propose":[4,58],"the":[5,17,26,33,61,67,70,74,78,83,92,122],"application":[6],"of":[7,28,66,85,108,118,124],"state-of-the-art":[8],"feature":[9,46,72],"descriptors":[10],"into":[11],"a":[12,37,45,53,89,96,115],"Particle":[13],"Filter":[14],"framework":[15],"for":[16,120],"lane":[18,125],"detection":[19],"task.":[20],"The":[21],"key":[22],"idea":[23],"lies":[24],"on":[25,52],"comparison":[27],"image":[29],"features":[30,75],"extracted":[31,50],"from":[32,77],"actual":[34],"measurement":[35],"with":[36],"priori":[38],"calculated":[39,76],"descriptors.":[40],"First,":[41],"demonstrate":[43],"how":[44],"expectation":[47],"can":[48],"be":[49],"based":[51],"particle":[54],"hypothesis.":[55],"We":[56,81,98],"then":[57],"to":[59],"define":[60],"likelihood":[62],"function":[63],"in":[64,106],"terms":[65,107],"distance":[68,94],"between":[69],"expected":[71],"and":[73,91,111],"current":[79],"measurement.":[80],"select":[82],"Histogram":[84],"Oriented":[86],"Gradients":[87],"as":[88,95],"descriptor":[90],"Battacharyya":[93],"metric.":[97],"show":[99],"that":[100,112],"simple":[102],"approach":[103],"is":[104],"powerful":[105],"pattern":[109],"discrimination":[110],"it":[113],"opens":[114],"new":[116],"set":[117],"possibilities":[119],"increasing":[121],"robustness":[123],"detectors.":[126]},"counts_by_year":[{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":3},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":4},{"year":2013,"cited_by_count":3}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
