{"id":"https://openalex.org/W2046356300","doi":"https://doi.org/10.1109/icip.2010.5653862","title":"Hierarchical method for foreground detection using codebook model","display_name":"Hierarchical method for foreground detection using codebook model","publication_year":2010,"publication_date":"2010-09-01","ids":{"openalex":"https://openalex.org/W2046356300","doi":"https://doi.org/10.1109/icip.2010.5653862","mag":"2046356300"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2010.5653862","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2010.5653862","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 Image 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/A5089868194","display_name":"Jing-Ming Guo","orcid":"https://orcid.org/0000-0002-8041-6326"},"institutions":[{"id":"https://openalex.org/I154864474","display_name":"National Taiwan University of Science and Technology","ror":"https://ror.org/00q09pe49","country_code":"TW","type":"education","lineage":["https://openalex.org/I154864474"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Jing-Ming Guo","raw_affiliation_strings":["Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan","[Department of Electrical Engineering, National-Taiwan University of Science and Technology, Taipei, Taiwan]"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan","institution_ids":["https://openalex.org/I154864474"]},{"raw_affiliation_string":"[Department of Electrical Engineering, National-Taiwan University of Science and Technology, Taipei, Taiwan]","institution_ids":["https://openalex.org/I154864474"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067241314","display_name":"Chih\u2010Sheng Hsu","orcid":null},"institutions":[{"id":"https://openalex.org/I154864474","display_name":"National Taiwan University of Science and Technology","ror":"https://ror.org/00q09pe49","country_code":"TW","type":"education","lineage":["https://openalex.org/I154864474"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chih-Sheng Hsu","raw_affiliation_strings":["Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan","[Department of Electrical Engineering, National-Taiwan University of Science and Technology, Taipei, Taiwan]"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan","institution_ids":["https://openalex.org/I154864474"]},{"raw_affiliation_string":"[Department of Electrical Engineering, National-Taiwan University of Science and Technology, Taipei, Taiwan]","institution_ids":["https://openalex.org/I154864474"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5089868194"],"corresponding_institution_ids":["https://openalex.org/I154864474"],"apc_list":null,"apc_paid":null,"fwci":0.64022473,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.70032737,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"3441","last_page":"3444"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9990000128746033,"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":0.9990000128746033,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9929999709129333,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9861999750137329,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/codebook","display_name":"Codebook","score":0.9627571105957031},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7825860977172852},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5724455118179321},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5185004472732544},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.4722138047218323},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.4503468871116638},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.44983041286468506},{"id":"https://openalex.org/keywords/linde\u2013buzo\u2013gray-algorithm","display_name":"Linde\u2013Buzo\u2013Gray algorithm","score":0.44079387187957764},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42536839842796326},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.40996596217155457},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3981955051422119},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1551806926727295}],"concepts":[{"id":"https://openalex.org/C127759330","wikidata":"https://www.wikidata.org/wiki/Q637416","display_name":"Codebook","level":2,"score":0.9627571105957031},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7825860977172852},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5724455118179321},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5185004472732544},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.4722138047218323},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.4503468871116638},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.44983041286468506},{"id":"https://openalex.org/C93372532","wikidata":"https://www.wikidata.org/wiki/Q6552455","display_name":"Linde\u2013Buzo\u2013Gray algorithm","level":3,"score":0.44079387187957764},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42536839842796326},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.40996596217155457},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3981955051422119},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1551806926727295},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"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/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2010.5653862","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2010.5653862","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 Image Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.7900000214576721,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1484372434","https://openalex.org/W1965214896","https://openalex.org/W1991848143","https://openalex.org/W2002103521","https://openalex.org/W2026938603","https://openalex.org/W2098305432","https://openalex.org/W2102625004","https://openalex.org/W2111918405","https://openalex.org/W2134288846","https://openalex.org/W2135879701","https://openalex.org/W2138187652","https://openalex.org/W2141572457","https://openalex.org/W2143373691","https://openalex.org/W2148290050","https://openalex.org/W2150634088","https://openalex.org/W2154128995","https://openalex.org/W2158604775","https://openalex.org/W2161932890","https://openalex.org/W2164734564","https://openalex.org/W2166843422","https://openalex.org/W3094885158","https://openalex.org/W4285719527","https://openalex.org/W6680014113"],"related_works":["https://openalex.org/W2096936443","https://openalex.org/W2081863301","https://openalex.org/W2352648934","https://openalex.org/W1977098967","https://openalex.org/W2365109233","https://openalex.org/W145510127","https://openalex.org/W2374856816","https://openalex.org/W2378932494","https://openalex.org/W2017514583","https://openalex.org/W2352292447"],"abstract_inverted_index":{"This":[0,134],"study":[1,111],"presents":[2,113],"a":[3,45,114],"new":[4,115],"hierarchical":[5],"scheme":[6],"with":[7,130,139],"coarse":[8,36,69,107],"level":[9,12,70,91,98,101],"and":[10,58,82,148],"fine":[11],"for":[13],"foreground":[14,129],"detection":[15],"using":[16],"codebook":[17],"model.":[18],"The":[19,47],"code":[20],"book":[21],"is":[22,71],"mainly":[23],"used":[24],"to":[25,28,43,145,166],"compress":[26],"information":[27],"achieve":[29],"high":[30],"efficient":[31],"processing":[32,64,80],"speed.":[33],"In":[34,66],"the":[35,50,53,68,131,140,156,159,169],"level,":[37],"six":[38],"intensity":[39],"values":[40],"are":[41],"employed":[42],"represent":[44],"block.":[46],"algorithm":[48,161],"extends":[49],"concept":[51],"of":[52,97,142,168],"Block":[54],"Truncation":[55],"Coding":[56],"(BTC),":[57],"thus":[59,149],"it":[60],"can":[61,78,93,102,119,136,162],"further":[62,103],"improve":[63],"efficiency.":[65],"detail,":[67],"divided":[72],"into":[73],"two":[74,92],"stages:":[75],"Level":[76],"one":[77],"increase":[79,94],"speed":[81],"reduce":[83],"noises":[84],"without":[85],"increasing":[86],"False":[87],"Positive":[88],"(FP)":[89],"rate;":[90],"detected":[95],"precision":[96,105],"one.":[99],"Fine":[100],"enhance":[104],"in":[106,155],"level.":[108],"Moreover,":[109],"this":[110],"also":[112,137],"color":[116],"model":[117,135],"which":[118],"classify":[120],"an":[121],"input":[122],"pixel":[123],"as":[124],"shadow,":[125],"highlight,":[126],"background,":[127],"or":[128],"match":[132],"function.":[133],"cooperate":[138],"Mixture":[141],"Gaussian":[143],"(MOG)":[144],"remove":[146],"shadow":[147],"enhances":[150],"MOG's":[151],"performance.":[152],"As":[153],"documented":[154],"experimental":[157],"results,":[158],"proposed":[160],"provide":[163],"superior":[164],"performance":[165],"that":[167],"former":[170],"Codebook":[171],"(CB)":[172],"approach.":[173]},"counts_by_year":[{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":6},{"year":2013,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}