{"id":"https://openalex.org/W2567382203","doi":"https://doi.org/10.1109/eusipco.2016.7760575","title":"Lipreading using spatiotemporal histogram of oriented gradients","display_name":"Lipreading using spatiotemporal histogram of oriented gradients","publication_year":2016,"publication_date":"2016-08-01","ids":{"openalex":"https://openalex.org/W2567382203","doi":"https://doi.org/10.1109/eusipco.2016.7760575","mag":"2567382203"},"language":"en","primary_location":{"id":"doi:10.1109/eusipco.2016.7760575","is_oa":false,"landing_page_url":"https://doi.org/10.1109/eusipco.2016.7760575","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 24th European Signal Processing Conference (EUSIPCO)","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/A5018875802","display_name":"Karel Pale\u010dek","orcid":"https://orcid.org/0000-0003-0693-6603"},"institutions":[{"id":"https://openalex.org/I147009085","display_name":"Technical University of Liberec","ror":"https://ror.org/02jtk7k02","country_code":"CZ","type":"education","lineage":["https://openalex.org/I147009085"]}],"countries":["CZ"],"is_corresponding":true,"raw_author_name":"Karel Palecek","raw_affiliation_strings":["The Institute of Information Technology and Electronics, Technical University of Liberec, Czech Republic"],"affiliations":[{"raw_affiliation_string":"The Institute of Information Technology and Electronics, Technical University of Liberec, Czech Republic","institution_ids":["https://openalex.org/I147009085"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5018875802"],"corresponding_institution_ids":["https://openalex.org/I147009085"],"apc_list":null,"apc_paid":null,"fwci":1.7653,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.86632131,"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":"1882","last_page":"1885"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9998000264167786,"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":0.9998000264167786,"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/T11448","display_name":"Face recognition and analysis","score":0.9976000189781189,"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":0.9789000153541565,"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/computer-science","display_name":"Computer science","score":0.7631374597549438},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.7279645204544067},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.7174167037010193},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6334507465362549},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6203721165657043},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.5980733633041382},{"id":"https://openalex.org/keywords/parametrization","display_name":"Parametrization (atmospheric modeling)","score":0.580715000629425},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5454214215278625},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5072329044342041},{"id":"https://openalex.org/keywords/histogram-of-oriented-gradients","display_name":"Histogram of oriented gradients","score":0.44339919090270996},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.10527640581130981}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7631374597549438},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.7279645204544067},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.7174167037010193},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6334507465362549},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6203721165657043},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.5980733633041382},{"id":"https://openalex.org/C202887219","wikidata":"https://www.wikidata.org/wiki/Q3895221","display_name":"Parametrization (atmospheric modeling)","level":3,"score":0.580715000629425},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5454214215278625},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5072329044342041},{"id":"https://openalex.org/C17426736","wikidata":"https://www.wikidata.org/wiki/Q419918","display_name":"Histogram of oriented gradients","level":4,"score":0.44339919090270996},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.10527640581130981},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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/C74902906","wikidata":"https://www.wikidata.org/wiki/Q1190858","display_name":"Radiative transfer","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/eusipco.2016.7760575","is_oa":false,"landing_page_url":"https://doi.org/10.1109/eusipco.2016.7760575","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 24th European Signal Processing Conference (EUSIPCO)","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":16,"referenced_works":["https://openalex.org/W36949327","https://openalex.org/W1908566903","https://openalex.org/W1990937109","https://openalex.org/W2051676197","https://openalex.org/W2060510034","https://openalex.org/W2077965293","https://openalex.org/W2098923380","https://openalex.org/W2136155248","https://openalex.org/W2138527036","https://openalex.org/W2142075667","https://openalex.org/W2161969291","https://openalex.org/W2169416477","https://openalex.org/W2408492884","https://openalex.org/W2612434330","https://openalex.org/W6639996154","https://openalex.org/W6713845897"],"related_works":["https://openalex.org/W2071599417","https://openalex.org/W2048716406","https://openalex.org/W1870444468","https://openalex.org/W2979608518","https://openalex.org/W1964725559","https://openalex.org/W2767833206","https://openalex.org/W3109748140","https://openalex.org/W2045053268","https://openalex.org/W2433492094","https://openalex.org/W1556327589"],"abstract_inverted_index":{"We":[0,61,95],"propose":[1],"a":[2,66],"visual":[3],"speech":[4],"parametrization":[5,83],"based":[6,68],"on":[7,69,98,135],"histogram":[8],"of":[9,16,26,103,118],"oriented":[10],"gradients":[11],"(HOG)":[12],"for":[13],"the":[14,24,31,41,116],"task":[15],"lipreading":[17],"from":[18,50],"frontal":[19],"face":[20],"videos.":[21],"Inspired":[22],"by":[23,45,77],"success":[25],"spatiotemporal":[27],"local":[28],"binary":[29],"patterns,":[30],"features":[32,64],"are":[33,105],"designed":[34],"to":[35,93,110],"capture":[36],"dynamic":[37],"information":[38],"contained":[39],"in":[40],"input":[42],"video":[43],"sequence":[44],"combining":[46],"HOG":[47],"descriptors":[48],"extracted":[49],"three":[51,99],"orthogonal":[52],"planes":[53],"that":[54,76],"span":[55],"x,":[56],"y":[57],"and":[58,74,80],"t":[59],"axes.":[60],"integrate":[62],"our":[63],"into":[65],"system":[67],"hidden":[70],"Markov":[71],"model":[72,119],"(HMM)":[73],"show":[75],"utilizing":[78],"robust":[79],"properly":[81],"tuned":[82],"this":[84,130],"traditional":[85],"scheme":[86],"can":[87],"outperform":[88],"recent":[89],"sophisticated":[90],"embedding":[91],"approaches":[92],"lipreading.":[94],"perform":[96],"experiments":[97],"different":[100],"datasets,":[101],"two":[102],"which":[104],"publicly":[106],"available.":[107],"In":[108],"order":[109],"conduct":[111],"an":[112],"unbiased":[113],"feature":[114],"comparison,":[115],"process":[117],"learning":[120],"including":[121],"hyperparameter":[122],"tuning":[123],"is":[124],"as":[125,127],"automatized":[126],"possible.":[128],"To":[129],"end,":[131],"we":[132],"rely":[133],"heavily":[134],"cross":[136],"validation.":[137]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}