{"id":"https://openalex.org/W2159213092","doi":"https://doi.org/10.1109/cvpr.2009.5206590","title":"Contextual classification with functional Max-Margin Markov Networks","display_name":"Contextual classification with functional Max-Margin Markov Networks","publication_year":2009,"publication_date":"2009-06-01","ids":{"openalex":"https://openalex.org/W2159213092","doi":"https://doi.org/10.1109/cvpr.2009.5206590","mag":"2159213092"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2009.5206590","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2009.5206590","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","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://figshare.com/articles/journal_contribution/Contextual_Classification_with_Functional_Max-Margin_Markov_Networks/6552392","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5037345774","display_name":"Daniel Urda","orcid":"https://orcid.org/0000-0003-2662-798X"},"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":"Daniel Munoz","raw_affiliation_strings":["The Robotics Institute, Carnegie Mellon University, USA"],"affiliations":[{"raw_affiliation_string":"The Robotics Institute, Carnegie Mellon University, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112411386","display_name":"J. Andrew Bagnell","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":false,"raw_author_name":"J. Andrew Bagnell","raw_affiliation_strings":["The Robotics Institute, Carnegie Mellon University, USA"],"affiliations":[{"raw_affiliation_string":"The Robotics Institute, Carnegie Mellon University, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018701857","display_name":"Nicolas Vandapel","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":false,"raw_author_name":"Nicolas Vandapel","raw_affiliation_strings":["The Robotics Institute, Carnegie Mellon University, USA"],"affiliations":[{"raw_affiliation_string":"The Robotics Institute, Carnegie Mellon University, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075246991","display_name":"Martial Hebert","orcid":"https://orcid.org/0000-0003-4566-5930"},"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":false,"raw_author_name":"Martial Hebert","raw_affiliation_strings":["The Robotics Institute, Carnegie Mellon University, USA"],"affiliations":[{"raw_affiliation_string":"The Robotics Institute, Carnegie Mellon University, USA","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5037345774"],"corresponding_institution_ids":["https://openalex.org/I74973139"],"apc_list":null,"apc_paid":null,"fwci":60.6695,"has_fulltext":true,"cited_by_count":308,"citation_normalized_percentile":{"value":1.0,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"975","last_page":"982"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9994000196456909,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9983000159263611,"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":0.7561190128326416},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7038123607635498},{"id":"https://openalex.org/keywords/generality","display_name":"Generality","score":0.6815622448921204},{"id":"https://openalex.org/keywords/conditional-random-field","display_name":"Conditional random field","score":0.6554775238037109},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.5877030491828918},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.5698776841163635},{"id":"https://openalex.org/keywords/markov-random-field","display_name":"Markov random field","score":0.5599018335342407},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.518964946269989},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5138276219367981},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.49534884095191956},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.4866815209388733},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.4665828347206116},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44704747200012207},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.44442301988601685},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4313238263130188},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.29782602190971375},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.17142364382743835},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14064520597457886}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7561190128326416},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7038123607635498},{"id":"https://openalex.org/C2780767217","wikidata":"https://www.wikidata.org/wiki/Q5532421","display_name":"Generality","level":2,"score":0.6815622448921204},{"id":"https://openalex.org/C152565575","wikidata":"https://www.wikidata.org/wiki/Q1124538","display_name":"Conditional random field","level":2,"score":0.6554775238037109},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.5877030491828918},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.5698776841163635},{"id":"https://openalex.org/C2778045648","wikidata":"https://www.wikidata.org/wiki/Q176827","display_name":"Markov random field","level":4,"score":0.5599018335342407},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.518964946269989},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5138276219367981},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.49534884095191956},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.4866815209388733},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.4665828347206116},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44704747200012207},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.44442301988601685},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4313238263130188},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.29782602190971375},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.17142364382743835},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14064520597457886},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C542102704","wikidata":"https://www.wikidata.org/wiki/Q183257","display_name":"Psychotherapist","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.1109/cvpr.2009.5206590","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2009.5206590","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:figshare.com:article/6552392","is_oa":true,"landing_page_url":null,"pdf_url":"https://figshare.com/articles/journal_contribution/Contextual_Classification_with_Functional_Max-Margin_Markov_Networks/6552392","source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"},{"id":"pmh:oai:repository.cmu.edu:robotics-1039","is_oa":false,"landing_page_url":"http://repository.cmu.edu/robotics/40","pdf_url":null,"source":{"id":"https://openalex.org/S4306400668","display_name":"Research Showcase @ Carnegie Mellon University (Carnegie Mellon University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I74973139","host_organization_name":"Carnegie Mellon University","host_organization_lineage":["https://openalex.org/I74973139"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Robotics Institute","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.150.2157","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.150.2157","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.cmu.edu/~dmunoz/pubs/munoz_cvpr_09.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.914.7437","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.914.7437","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://repository.cmu.edu/cgi/viewcontent.cgi?article%3D1039%26context%3Drobotics","raw_type":"text"},{"id":"doi:10.1184/r1/6552392.v1","is_oa":true,"landing_page_url":"https://doi.org/10.1184/r1/6552392.v1","pdf_url":null,"source":{"id":"https://openalex.org/S7407050927","display_name":"KiltHub Repository","issn_l":null,"issn":[],"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":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article-journal"}],"best_oa_location":{"id":"pmh:oai:figshare.com:article/6552392","is_oa":true,"landing_page_url":null,"pdf_url":"https://figshare.com/articles/journal_contribution/Contextual_Classification_with_Functional_Max-Margin_Markov_Networks/6552392","source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320315933","display_name":"Siebel Scholars Foundation","ror":null},{"id":"https://openalex.org/F4320320875","display_name":"Deutscher Akademischer Austauschdienst","ror":"https://ror.org/039djdh30"},{"id":"https://openalex.org/F4320338295","display_name":"Army Research Laboratory","ror":"https://ror.org/011hc8f90"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2159213092.pdf","grobid_xml":"https://content.openalex.org/works/W2159213092.grobid-xml"},"referenced_works_count":45,"referenced_works":["https://openalex.org/W1484011530","https://openalex.org/W1506176787","https://openalex.org/W1516657904","https://openalex.org/W1561326744","https://openalex.org/W1586342396","https://openalex.org/W1678356000","https://openalex.org/W1792316426","https://openalex.org/W1964803612","https://openalex.org/W2099608971","https://openalex.org/W2105644991","https://openalex.org/W2106122512","https://openalex.org/W2107640784","https://openalex.org/W2115703234","https://openalex.org/W2116877738","https://openalex.org/W2120247405","https://openalex.org/W2125310925","https://openalex.org/W2126105931","https://openalex.org/W2128680590","https://openalex.org/W2130513366","https://openalex.org/W2132947399","https://openalex.org/W2140789035","https://openalex.org/W2143516773","https://openalex.org/W2147880316","https://openalex.org/W2147937146","https://openalex.org/W2150408100","https://openalex.org/W2158388185","https://openalex.org/W2161160262","https://openalex.org/W2163246736","https://openalex.org/W2544683879","https://openalex.org/W3094928914","https://openalex.org/W4252621450","https://openalex.org/W6629061536","https://openalex.org/W6633624968","https://openalex.org/W6635188717","https://openalex.org/W6638388375","https://openalex.org/W6675004785","https://openalex.org/W6675760969","https://openalex.org/W6676328599","https://openalex.org/W6679459161","https://openalex.org/W6680866351","https://openalex.org/W6681785842","https://openalex.org/W6682082992","https://openalex.org/W6683372824","https://openalex.org/W6683692026","https://openalex.org/W6729118241"],"related_works":["https://openalex.org/W2048280290","https://openalex.org/W2546871836","https://openalex.org/W2136485282","https://openalex.org/W4308191010","https://openalex.org/W4323021782","https://openalex.org/W2911455822","https://openalex.org/W3174196512","https://openalex.org/W2964383635","https://openalex.org/W2159213092","https://openalex.org/W4234190238"],"abstract_inverted_index":{"We":[0,102],"address":[1],"the":[2,34,97,104,107,115,118,125,128,131],"problem":[3,134],"of":[4,45,74,109,117,127,135],"label":[5,23],"assignment":[6],"in":[7,77,106],"computer":[8],"vision:":[9],"given":[10],"a":[11,21,43,66],"novel":[12],"3D":[13],"or":[14],"2D":[15],"scene,":[16],"we":[17,64,87,122],"wish":[18],"to":[19,24,41,52,79],"assign":[20],"unique":[22],"every":[25],"site":[26],"(voxel,":[27],"pixel,":[28],"superpixel,":[29],"etc.).":[30],"To":[31],"this":[32,62,85],"end,":[33],"Markov":[35],"Random":[36],"Field":[37],"framework":[38],"has":[39],"proven":[40],"be":[42],"model":[44],"choice":[46],"as":[47],"it":[48],"uses":[49],"contextual":[50],"information":[51],"yield":[53],"improved":[54],"classification":[55,112],"results":[56],"over":[57],"locally":[58],"independent":[59],"classifiers.":[60],"In":[61,120],"work":[63],"adapt":[65],"functional":[67],"gradient":[68],"approach":[69,86,105,129],"for":[70],"learning":[71,100],"high-dimensional":[72],"parameters":[73],"random":[75],"fields":[76],"order":[78],"perform":[80],"discrete,":[81],"multi-label":[82],"classification.":[83],"With":[84],"can":[88],"learn":[89],"robust":[90],"models":[91],"involving":[92],"high-order":[93],"interactions":[94],"better":[95],"than":[96],"previously":[98],"used":[99],"method.":[101],"validate":[103],"context":[108],"point":[110],"cloud":[111],"and":[113],"improve":[114],"state":[116],"art.":[119],"addition,":[121],"successfully":[123],"demonstrate":[124],"generality":[126],"on":[130],"challenging":[132],"vision":[133],"recovering":[136],"3-D":[137],"geometric":[138],"surfaces":[139],"from":[140],"images.":[141]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":24},{"year":2022,"cited_by_count":12},{"year":2021,"cited_by_count":29},{"year":2020,"cited_by_count":39},{"year":2019,"cited_by_count":27},{"year":2018,"cited_by_count":20},{"year":2017,"cited_by_count":19},{"year":2016,"cited_by_count":13},{"year":2015,"cited_by_count":23},{"year":2014,"cited_by_count":24},{"year":2013,"cited_by_count":16},{"year":2012,"cited_by_count":14}],"updated_date":"2026-04-18T07:56:08.524223","created_date":"2025-10-10T00:00:00"}