{"id":"https://openalex.org/W2167208151","doi":"https://doi.org/10.1109/icassp.2010.5495373","title":"Lip tracking using adaptive fuzzy particle filter in the context of car driving simulator under low contrast near-infrared illumination","display_name":"Lip tracking using adaptive fuzzy particle filter in the context of car driving simulator under low contrast near-infrared illumination","publication_year":2010,"publication_date":"2010-01-01","ids":{"openalex":"https://openalex.org/W2167208151","doi":"https://doi.org/10.1109/icassp.2010.5495373","mag":"2167208151"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2010.5495373","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2010.5495373","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE International Conference on Acoustics, Speech and Signal Processing","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/A5005258803","display_name":"Parisa Darvish Zadeh Varcheie","orcid":null},"institutions":[{"id":"https://openalex.org/I4210111842","display_name":"Computer Research Institute of Montr\u00e9al","ror":"https://ror.org/0279d5115","country_code":"CA","type":"nonprofit","lineage":["https://openalex.org/I4210111842"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Parisa Darvish Zadeh Varcheie","raw_affiliation_strings":["R & D Department, CRIM, Montreal, QUE, Canada"],"affiliations":[{"raw_affiliation_string":"R & D Department, CRIM, Montreal, QUE, Canada","institution_ids":["https://openalex.org/I4210111842"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111999490","display_name":"Langis Gagnon","orcid":null},"institutions":[{"id":"https://openalex.org/I4210111842","display_name":"Computer Research Institute of Montr\u00e9al","ror":"https://ror.org/0279d5115","country_code":"CA","type":"nonprofit","lineage":["https://openalex.org/I4210111842"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Langis Gagnon","raw_affiliation_strings":["R & D Department, CRIM, Montreal, QUE, Canada"],"affiliations":[{"raw_affiliation_string":"R & D Department, CRIM, Montreal, QUE, Canada","institution_ids":["https://openalex.org/I4210111842"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5005258803"],"corresponding_institution_ids":["https://openalex.org/I4210111842"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.21080275,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1162","last_page":"1165"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9933000206947327,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10860","display_name":"Speech and Audio Processing","score":0.9933000206947327,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.9908999800682068,"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/T11448","display_name":"Face recognition and analysis","score":0.975600004196167,"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/particle-filter","display_name":"Particle filter","score":0.8251274824142456},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.7338671684265137},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.607596755027771},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.5826454758644104},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5814047455787659},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5667717456817627},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.5397433042526245},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5003538131713867},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4839742183685303},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.47413942217826843},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.10733231902122498}],"concepts":[{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.8251274824142456},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.7338671684265137},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.607596755027771},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.5826454758644104},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5814047455787659},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5667717456817627},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.5397433042526245},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5003538131713867},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4839742183685303},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.47413942217826843},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.10733231902122498},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"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/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2010.5495373","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2010.5495373","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE International Conference on Acoustics, Speech and Signal Processing","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":12,"referenced_works":["https://openalex.org/W1927399054","https://openalex.org/W1952910563","https://openalex.org/W2102880020","https://openalex.org/W2143549765","https://openalex.org/W2147939865","https://openalex.org/W2153621257","https://openalex.org/W2402700212","https://openalex.org/W2995034616","https://openalex.org/W4249348869","https://openalex.org/W4285719527","https://openalex.org/W6640766037","https://openalex.org/W6771710517"],"related_works":["https://openalex.org/W1989212443","https://openalex.org/W2103644279","https://openalex.org/W4302986566","https://openalex.org/W1968585197","https://openalex.org/W2135362996","https://openalex.org/W2150578674","https://openalex.org/W877199042","https://openalex.org/W2122155275","https://openalex.org/W4247544095","https://openalex.org/W2535707089"],"abstract_inverted_index":{"A":[0],"real-time":[1],"lip":[2,68,110,122],"tracking":[3,62,89],"on":[4,23,81],"very":[5],"low":[6],"contrast":[7],"images":[8],"acquired":[9],"under":[10],"near-infrared":[11],"illumination":[12],"is":[13,27,40,91],"presented.":[14],"We":[15],"developed":[16],"a":[17,71,82],"modified":[18],"particle":[19,45,72],"filter":[20,46,73],"tracker":[21],"based":[22,80],"fuzzy":[24,83],"logic":[25],"that":[26],"appropriate":[28],"for":[29,93],"non-linear":[30],"modeling":[31,60],"and":[32,56,61,74,103],"robust":[33],"to":[34,42,54],"the":[35,44,88,109,121,125],"non-Gaussian":[36],"noise.":[37],"Fuzzy":[38,49],"model":[39],"used":[41],"normalize":[43],"samples":[47],"weights.":[48],"membership":[50],"functions":[51],"are":[52,63,78,112],"applied":[53],"geometric":[55],"appearance":[57],"features.":[58],"Lip":[59],"done":[64,79],"by":[65],"sampling":[66],"around":[67],"regions":[69],"using":[70],"scoring":[75],"sample":[76],"features":[77],"rule.":[84],"The":[85],"performance":[86],"of":[87,108,120],"algorithm":[90],"evaluated":[92],"different":[94],"people":[95],"with":[96],"various":[97],"mouth":[98],"changes,":[99],"such":[100],"as":[101],"smile":[102],"speech.":[104],"More":[105],"than":[106,118],"78%":[107],"corners":[111],"correctly":[113],"detected":[114],"within":[115],"distances":[116],"less":[117],"5%":[119],"length":[123],"from":[124],"ground":[126],"truth.":[127]},"counts_by_year":[{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}