{"id":"https://openalex.org/W2540969864","doi":"https://doi.org/10.1109/acpr.2011.6166545","title":"Video Object Segmentation by Hierarchical Localized Classification of Regions","display_name":"Video Object Segmentation by Hierarchical Localized Classification of Regions","publication_year":2011,"publication_date":"2011-11-01","ids":{"openalex":"https://openalex.org/W2540969864","doi":"https://doi.org/10.1109/acpr.2011.6166545","mag":"2540969864"},"language":"en","primary_location":{"id":"doi:10.1109/acpr.2011.6166545","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acpr.2011.6166545","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The First Asian Conference on 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/A5000378281","display_name":"Chenguang Zhang","orcid":"https://orcid.org/0000-0002-5665-6397"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chenguang Zhang","raw_affiliation_strings":["Department of Computer Science and Technology, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074577884","display_name":"Haizhou Ai","orcid":"https://orcid.org/0000-0002-0166-5755"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haizhou Ai","raw_affiliation_strings":["Department of Computer Science and Technology, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5000378281"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.33652221,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"28","issue":null,"first_page":"244","last_page":"248"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9998000264167786,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9994999766349792,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.777259349822998},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7463692426681519},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6813485622406006},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6359052062034607},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.5768669843673706},{"id":"https://openalex.org/keywords/clutter","display_name":"Clutter","score":0.5522748827934265},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5488914251327515},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5286415219306946},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.44153285026550293},{"id":"https://openalex.org/keywords/coherence","display_name":"Coherence (philosophical gambling strategy)","score":0.4239000082015991},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15537932515144348},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.08342525362968445}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.777259349822998},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7463692426681519},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6813485622406006},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6359052062034607},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.5768669843673706},{"id":"https://openalex.org/C132094186","wikidata":"https://www.wikidata.org/wiki/Q641585","display_name":"Clutter","level":3,"score":0.5522748827934265},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5488914251327515},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5286415219306946},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.44153285026550293},{"id":"https://openalex.org/C2781181686","wikidata":"https://www.wikidata.org/wiki/Q4226068","display_name":"Coherence (philosophical gambling strategy)","level":2,"score":0.4239000082015991},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15537932515144348},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.08342525362968445},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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/acpr.2011.6166545","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acpr.2011.6166545","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The First Asian Conference on Pattern Recognition","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.294.4600","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.294.4600","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://media.cs.tsinghua.edu.cn/~imagevision/papers/[2011][acpr]zhang chenguang.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.6700000166893005}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1510601258","https://openalex.org/W1607197324","https://openalex.org/W1964443764","https://openalex.org/W1975862670","https://openalex.org/W1995903777","https://openalex.org/W2030346542","https://openalex.org/W2102354443","https://openalex.org/W2124351162","https://openalex.org/W2125907508","https://openalex.org/W2152632881","https://openalex.org/W2162152641","https://openalex.org/W2163747463","https://openalex.org/W2169551590","https://openalex.org/W2170865122","https://openalex.org/W6630493829"],"related_works":["https://openalex.org/W2130674020","https://openalex.org/W2093748878","https://openalex.org/W2333771223","https://openalex.org/W2120056845","https://openalex.org/W1981531423","https://openalex.org/W4394861761","https://openalex.org/W1977371217","https://openalex.org/W2035264131","https://openalex.org/W1679012645","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Video":[0],"Object":[1],"Segmentation":[2],"(VOS)":[3],"is":[4],"to":[5,62,69,75],"cut":[6],"out":[7],"a":[8,33,104],"selected":[9],"object":[10],"from":[11],"video":[12,121],"sequences,":[13],"where":[14],"the":[15,52,60,98,110,124,129],"main":[16],"difficulties":[17],"are":[18,59],"shape":[19],"deformation,":[20],"appearance":[21,47],"variations":[22],"and":[23,54,100,126],"background":[24],"clutter.":[25],"To":[26],"cope":[27],"with":[28],"these":[29],"difficulties,":[30],"we":[31,73,89,107],"propose":[32,74],"novel":[34],"method,":[35],"named":[36],"as":[37,49,51,84],"Hierarchical":[38],"Localized":[39,78],"Classification":[40],"of":[41,128],"Regions":[42],"(HLCR).":[43],"We":[44],"suggest":[45],"that":[46],"models":[48],"well":[50],"spatial":[53],"temporal":[55],"coherence":[56],"between":[57],"frames":[58],"keys":[61],"break":[63],"through":[64],"bottleneck.":[65],"Locally,":[66],"in":[67],"order":[68],"identify":[70],"foreground":[71],"regions,":[72],"use":[76],"Hierarchial":[77],"Classifiers,":[79],"which":[80],"organize":[81],"regional":[82],"features":[83],"decision":[85],"trees.":[86],"In":[87],"global,":[88],"adopt":[90],"Gaussian":[91],"Mixture":[92],"Color":[93],"Models":[94],"(GMMs).":[95],"After":[96],"integrating":[97],"local":[99],"global":[101],"results":[102],"into":[103],"probability":[105],"mask,":[106],"can":[108],"achieve":[109],"final":[111],"segmentation":[112],"result":[113],"by":[114],"graph":[115],"cut.":[116],"Experiments":[117],"on":[118],"various":[119],"challenging":[120],"sequences":[122],"demonstrate":[123],"efficiency":[125],"adaptability":[127],"proposed":[130],"method.":[131]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}