{"id":"https://openalex.org/W2137971795","doi":"https://doi.org/10.1109/cvpr.2009.5206549","title":"Unsupervised learning of hierarchical spatial structures in images","display_name":"Unsupervised learning of hierarchical spatial structures in images","publication_year":2009,"publication_date":"2009-06-01","ids":{"openalex":"https://openalex.org/W2137971795","doi":"https://doi.org/10.1109/cvpr.2009.5206549","mag":"2137971795"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2009.5206549","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2009.5206549","pdf_url":null,"source":{"id":"https://openalex.org/S4363607795","display_name":"2009 IEEE Conference on Computer Vision and Pattern Recognition","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 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/A5050342343","display_name":"Devi Parikh","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Devi Parikh","raw_affiliation_strings":["Carnegie Mellon University, Pittsburgh, PA, USA","Carnegie-Mellon University, Pittsburgh, Pa., USA#TAB#"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]},{"raw_affiliation_string":"Carnegie-Mellon University, Pittsburgh, Pa., USA#TAB#","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058450549","display_name":"C. Lawrence Zitnick","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":"C. Lawrence Zitnick","raw_affiliation_strings":["Microsoft Research Limited, Redmond, WA, USA","[Microsoft Research,Redmond,WA,USA]"],"affiliations":[{"raw_affiliation_string":"Microsoft Research Limited, Redmond, WA, USA","institution_ids":["https://openalex.org/I1290206253"]},{"raw_affiliation_string":"[Microsoft Research,Redmond,WA,USA]","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000454484","display_name":"Tsuhan Chen","orcid":"https://orcid.org/0000-0003-3951-7931"},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tsuhan Chen","raw_affiliation_strings":["Cornell University, Ithaca, NY, USA","Cornell Univ, Ithaca, NY, USA"],"affiliations":[{"raw_affiliation_string":"Cornell University, Ithaca, NY, USA","institution_ids":["https://openalex.org/I205783295"]},{"raw_affiliation_string":"Cornell Univ, Ithaca, NY, USA","institution_ids":["https://openalex.org/I205783295"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5050342343"],"corresponding_institution_ids":["https://openalex.org/I74973139"],"apc_list":null,"apc_paid":null,"fwci":2.115,"has_fulltext":false,"cited_by_count":32,"citation_normalized_percentile":{"value":0.8940754,"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":"2743","last_page":"2750"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","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"}},"topics":[{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","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"}},{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9886999726295471,"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/computer-science","display_name":"Computer science","score":0.7193480134010315},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6706832647323608},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5955587029457092},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5913515686988831},{"id":"https://openalex.org/keywords/hierarchy","display_name":"Hierarchy","score":0.5895726084709167},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5058998465538025},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.5049973130226135},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.48732051253318787},{"id":"https://openalex.org/keywords/object-based-spatial-database","display_name":"Object-based spatial database","score":0.48523855209350586},{"id":"https://openalex.org/keywords/directed-acyclic-graph","display_name":"Directed acyclic graph","score":0.45668402314186096},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44135037064552307},{"id":"https://openalex.org/keywords/tree-structure","display_name":"Tree structure","score":0.43413305282592773},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.27735522389411926},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.2512006163597107},{"id":"https://openalex.org/keywords/data-structure","display_name":"Data structure","score":0.2261648178100586},{"id":"https://openalex.org/keywords/spatial-database","display_name":"Spatial database","score":0.2013045847415924},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16239312291145325},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.11968839168548584}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7193480134010315},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6706832647323608},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5955587029457092},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5913515686988831},{"id":"https://openalex.org/C31170391","wikidata":"https://www.wikidata.org/wiki/Q188619","display_name":"Hierarchy","level":2,"score":0.5895726084709167},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5058998465538025},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.5049973130226135},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.48732051253318787},{"id":"https://openalex.org/C153938966","wikidata":"https://www.wikidata.org/wiki/Q3348148","display_name":"Object-based spatial database","level":4,"score":0.48523855209350586},{"id":"https://openalex.org/C74197172","wikidata":"https://www.wikidata.org/wiki/Q1195339","display_name":"Directed acyclic graph","level":2,"score":0.45668402314186096},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44135037064552307},{"id":"https://openalex.org/C163797641","wikidata":"https://www.wikidata.org/wiki/Q2067937","display_name":"Tree structure","level":3,"score":0.43413305282592773},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.27735522389411926},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2512006163597107},{"id":"https://openalex.org/C162319229","wikidata":"https://www.wikidata.org/wiki/Q175263","display_name":"Data structure","level":2,"score":0.2261648178100586},{"id":"https://openalex.org/C203689450","wikidata":"https://www.wikidata.org/wiki/Q2302053","display_name":"Spatial database","level":3,"score":0.2013045847415924},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16239312291145325},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.11968839168548584},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C34447519","wikidata":"https://www.wikidata.org/wiki/Q179522","display_name":"Market economy","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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/cvpr.2009.5206549","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2009.5206549","pdf_url":null,"source":{"id":"https://openalex.org/S4363607795","display_name":"2009 IEEE Conference on Computer Vision and Pattern Recognition","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE Conference on Computer Vision and Pattern Recognition","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.156.2399","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.156.2399","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://research.microsoft.com/~larryz/SteinerCVPR2009.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.7599999904632568,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":55,"referenced_works":["https://openalex.org/W55191700","https://openalex.org/W168365783","https://openalex.org/W1566135517","https://openalex.org/W1594799244","https://openalex.org/W1821057786","https://openalex.org/W1968497507","https://openalex.org/W1999478155","https://openalex.org/W2009976792","https://openalex.org/W2030536784","https://openalex.org/W2061315523","https://openalex.org/W2074584543","https://openalex.org/W2081293863","https://openalex.org/W2098355199","https://openalex.org/W2099972257","https://openalex.org/W2103658758","https://openalex.org/W2107640784","https://openalex.org/W2110764733","https://openalex.org/W2113656553","https://openalex.org/W2117030034","https://openalex.org/W2121043743","https://openalex.org/W2121947440","https://openalex.org/W2124297750","https://openalex.org/W2125802042","https://openalex.org/W2126747264","https://openalex.org/W2128962821","https://openalex.org/W2134636339","https://openalex.org/W2134665698","https://openalex.org/W2137604611","https://openalex.org/W2140363548","https://openalex.org/W2142350269","https://openalex.org/W2142571543","https://openalex.org/W2145743319","https://openalex.org/W2146352414","https://openalex.org/W2151103935","https://openalex.org/W2154422044","https://openalex.org/W2156928353","https://openalex.org/W2157084238","https://openalex.org/W2162820221","https://openalex.org/W2163490908","https://openalex.org/W2166049352","https://openalex.org/W2168133252","https://openalex.org/W4233761317","https://openalex.org/W4241222664","https://openalex.org/W6611723228","https://openalex.org/W6635801470","https://openalex.org/W6642392778","https://openalex.org/W6674646328","https://openalex.org/W6675276727","https://openalex.org/W6676328599","https://openalex.org/W6677945368","https://openalex.org/W6678637433","https://openalex.org/W6678796163","https://openalex.org/W6680786152","https://openalex.org/W6680792852","https://openalex.org/W6681508479"],"related_works":["https://openalex.org/W4302345037","https://openalex.org/W2731094954","https://openalex.org/W2789273959","https://openalex.org/W1998712144","https://openalex.org/W2952978498","https://openalex.org/W4292730466","https://openalex.org/W2951616510","https://openalex.org/W2066802334","https://openalex.org/W2789847084","https://openalex.org/W3208293411"],"abstract_inverted_index":{"The":[0],"visual":[1],"world":[2],"demonstrates":[3],"organized":[4],"spatial":[5,26,38,62,76],"patterns,":[6,77],"among":[7],"objects":[8],"or":[9],"regions":[10],"in":[11,15,21,31,46,115,126],"a":[12,47,54,65,71,84,97,127,136],"scene,":[13],"object-parts":[14],"an":[16,88,116],"object,":[17],"and":[18,148],"low-level":[19],"features":[20],"object-parts.":[22],"These":[23],"classes":[24],"of":[25,43,60,67,99,107,111,139,142],"structures":[27,63],"are":[28,40],"inherently":[29],"hierarchical":[30,61,72],"nature.":[32],"Although":[33],"seemingly":[34],"quite":[35],"different":[36,44],"these":[37],"patterns":[39],"simply":[41],"manifestations":[42],"levels":[45],"hierarchy.":[48],"In":[49],"this":[50],"work,":[51],"we":[52],"present":[53],"unified":[55],"approach":[56,134],"to":[57,92,120],"unsupervised":[58,89],"learning":[59],"from":[64,96,150],"collection":[66,98],"images.":[68,100],"Ours":[69],"is":[70,81,118],"rule-based":[73],"model":[74,95],"capturing":[75],"where":[78],"each":[79],"rule":[80],"represented":[82],"by":[83],"star-graph.":[85],"We":[86,101,131],"propose":[87],"EM-style":[90],"algorithm":[91],"learn":[93],"our":[94,133],"show":[102],"that":[103],"the":[104,109,122],"inference":[105],"problem":[106],"determining":[108],"set":[110,138],"learnt":[112],"rules":[113],"instantiated":[114],"image":[117],"equivalent":[119],"finding":[121],"minimum-cost":[123],"Steiner":[124],"tree":[125],"directed":[128],"acyclic":[129],"graph.":[130],"evaluate":[132],"on":[135],"diverse":[137],"data":[140],"sets":[141],"object":[143],"categories,":[144],"natural":[145],"outdoor":[146],"scenes":[147,153],"images":[149],"complex":[151],"street":[152],"with":[154],"multiple":[155],"objects.":[156]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":6},{"year":2012,"cited_by_count":6}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}