{"id":"https://openalex.org/W2170563926","doi":"https://doi.org/10.1109/cvpr.2012.6247951","title":"A regularized spectral algorithm for Hidden Markov Models with applications in computer vision","display_name":"A regularized spectral algorithm for Hidden Markov Models with applications in computer vision","publication_year":2012,"publication_date":"2012-06-01","ids":{"openalex":"https://openalex.org/W2170563926","doi":"https://doi.org/10.1109/cvpr.2012.6247951","mag":"2170563926"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2012.6247951","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2012.6247951","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE Conference on Computer Vision and Pattern Recognition","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/A5007571091","display_name":"H\u00e0 Quang Minh","orcid":"https://orcid.org/0000-0003-3926-8875"},"institutions":[{"id":"https://openalex.org/I30771326","display_name":"Italian Institute of Technology","ror":"https://ror.org/042t93s57","country_code":"IT","type":"facility","lineage":["https://openalex.org/I30771326"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Ha Quang Minh","raw_affiliation_strings":["Istituto Italiano di Tecnologia, Genoa, Italy"],"affiliations":[{"raw_affiliation_string":"Istituto Italiano di Tecnologia, Genoa, Italy","institution_ids":["https://openalex.org/I30771326"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087797803","display_name":"Matteo Cristani","orcid":"https://orcid.org/0000-0001-5680-0080"},"institutions":[{"id":"https://openalex.org/I30771326","display_name":"Italian Institute of Technology","ror":"https://ror.org/042t93s57","country_code":"IT","type":"facility","lineage":["https://openalex.org/I30771326"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"M. Cristani","raw_affiliation_strings":["Istituto Italiano di Tecnologia, Genoa, Italy"],"affiliations":[{"raw_affiliation_string":"Istituto Italiano di Tecnologia, Genoa, Italy","institution_ids":["https://openalex.org/I30771326"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108685730","display_name":"Alessandro Perina","orcid":null},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"A. Perina","raw_affiliation_strings":["Microsoft Research, WA, USA"],"affiliations":[{"raw_affiliation_string":"Microsoft Research, WA, USA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007242502","display_name":"Vittorio Murino","orcid":"https://orcid.org/0000-0002-8645-2328"},"institutions":[{"id":"https://openalex.org/I30771326","display_name":"Italian Institute of Technology","ror":"https://ror.org/042t93s57","country_code":"IT","type":"facility","lineage":["https://openalex.org/I30771326"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"V. Murino","raw_affiliation_strings":["Istituto Italiano di Tecnologia, Genoa, Italy"],"affiliations":[{"raw_affiliation_string":"Istituto Italiano di Tecnologia, Genoa, Italy","institution_ids":["https://openalex.org/I30771326"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5007571091"],"corresponding_institution_ids":["https://openalex.org/I30771326"],"apc_list":null,"apc_paid":null,"fwci":1.0982,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.81109512,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"2384","last_page":"2391"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9959999918937683,"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/T10057","display_name":"Face and Expression Recognition","score":0.9959999918937683,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9947999715805054,"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":0.9939000010490417,"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/hidden-markov-model","display_name":"Hidden Markov model","score":0.8995108604431152},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6969352960586548},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6165699362754822},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6164371371269226},{"id":"https://openalex.org/keywords/maxima-and-minima","display_name":"Maxima and minima","score":0.5741313099861145},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5416216850280762},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4820617139339447},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.461594820022583},{"id":"https://openalex.org/keywords/viterbi-algorithm","display_name":"Viterbi algorithm","score":0.4546350836753845},{"id":"https://openalex.org/keywords/markov-model","display_name":"Markov model","score":0.44051462411880493},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.43328750133514404},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42730990052223206},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.35379114747047424},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21832656860351562}],"concepts":[{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.8995108604431152},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6969352960586548},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6165699362754822},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6164371371269226},{"id":"https://openalex.org/C186633575","wikidata":"https://www.wikidata.org/wiki/Q845060","display_name":"Maxima and minima","level":2,"score":0.5741313099861145},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5416216850280762},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4820617139339447},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.461594820022583},{"id":"https://openalex.org/C60582962","wikidata":"https://www.wikidata.org/wiki/Q83886","display_name":"Viterbi algorithm","level":3,"score":0.4546350836753845},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.44051462411880493},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.43328750133514404},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42730990052223206},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.35379114747047424},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21832656860351562},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cvpr.2012.6247951","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2012.6247951","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE Conference on Computer Vision and Pattern Recognition","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1508165687","https://openalex.org/W1536864280","https://openalex.org/W1540337045","https://openalex.org/W1587377726","https://openalex.org/W2009570821","https://openalex.org/W2086699924","https://openalex.org/W2097150846","https://openalex.org/W2102122585","https://openalex.org/W2125838338","https://openalex.org/W2137161518","https://openalex.org/W2141262001","https://openalex.org/W2149960632","https://openalex.org/W2170452183","https://openalex.org/W2569025259","https://openalex.org/W2950265833","https://openalex.org/W4245668478","https://openalex.org/W6632428414","https://openalex.org/W6638541763","https://openalex.org/W6674377085"],"related_works":["https://openalex.org/W2136652457","https://openalex.org/W2169849734","https://openalex.org/W2160171981","https://openalex.org/W2385954530","https://openalex.org/W1975869217","https://openalex.org/W2236912844","https://openalex.org/W2129150969","https://openalex.org/W2116722627","https://openalex.org/W2379938888","https://openalex.org/W3044198794"],"abstract_inverted_index":{"Hidden":[0],"Markov":[1],"Models":[2],"(HMMs)":[3],"are":[4,36,86,143],"among":[5],"the":[6,60,110,115,139],"most":[7],"important":[8],"and":[9,90,114,134,138],"widely":[10],"used":[11,144],"techniques":[12],"to":[13,29,81,100],"deal":[14],"with":[15,70],"sequential":[16],"or":[17,160],"temporal":[18],"data.":[19],"Their":[20],"application":[21],"in":[22,39,59,132,145],"computer":[23],"vision":[24,146],"ranges":[25],"from":[26],"action/gesture":[27],"recognition":[28,122],"videosurveillance":[30],"through":[31],"shape":[32],"analysis.":[33],"Although":[34],"HMMs":[35,58,142,168],"often":[37],"embedded":[38],"complex":[40,162],"frameworks,":[41],"this":[42],"paper":[43],"focuses":[44],"on":[45,92,109],"theoretical":[46],"aspects":[47],"of":[48,112,117],"HMM":[49],"learning.":[50],"We":[51],"propose":[52],"a":[53,171],"regularized":[54],"algorithm":[55,126],"for":[56,75,150,175],"learning":[57],"spectral":[61,73,167],"framework,":[62],"whose":[63],"computations":[64],"have":[65],"no":[66,107],"local":[67],"minima.":[68],"Compared":[69],"recently":[71],"proposed":[72],"algorithms":[74],"HMMs,":[76,130],"our":[77,125],"method":[78],"is":[79],"guaranteed":[80],"produce":[82],"probability":[83,102],"values":[84],"which":[85],"always":[87],"physically":[88],"meaningful":[89],"which,":[91],"synthetic":[93],"mathematical":[94],"models,":[95,164],"give":[96],"very":[97],"good":[98],"approximations":[99],"true":[101],"values.":[103],"Furthermore,":[104],"we":[105],"place":[106],"restriction":[108],"number":[111,116],"symbols":[113],"states.":[118],"On":[119],"various":[120],"pattern":[121,176],"data":[123],"sets,":[124],"consistently":[127],"outperforms":[128],"classical":[129],"both":[131],"accuracy":[133],"computational":[135],"speed.":[136],"This":[137],"fact":[140],"that":[141],"as":[147,156,170],"building":[148],"blocks":[149],"more":[151,161],"powerful":[152],"classification":[153],"approaches,":[154],"such":[155],"generative":[157,163],"embedding":[158],"approaches":[159],"strongly":[165],"support":[166],"(SHMMs)":[169],"new":[172],"basic":[173],"tool":[174],"recognition.":[177]},"counts_by_year":[{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
