{"id":"https://openalex.org/W2113201962","doi":"https://doi.org/10.1109/iccv.2011.6126264","title":"Segmentation from a box","display_name":"Segmentation from a box","publication_year":2011,"publication_date":"2011-11-01","ids":{"openalex":"https://openalex.org/W2113201962","doi":"https://doi.org/10.1109/iccv.2011.6126264","mag":"2113201962"},"language":"en","primary_location":{"id":"doi:10.1109/iccv.2011.6126264","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2011.6126264","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 International Conference on Computer Vision","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/A5084386176","display_name":"Leo Grady","orcid":null},"institutions":[{"id":"https://openalex.org/I4210137693","display_name":"Siemens (United States)","ror":"https://ror.org/04axb7e79","country_code":"US","type":"company","lineage":["https://openalex.org/I1325886976","https://openalex.org/I4210137693"]},{"id":"https://openalex.org/I20089843","display_name":"Princeton University","ror":"https://ror.org/00hx57361","country_code":"US","type":"education","lineage":["https://openalex.org/I20089843"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Leo Grady","raw_affiliation_strings":["Siemens Corporate Research, Image Analytics and Informatics, Princeton, NJ, USA","Siemens Corporate Research-Image Analytics and Informatics, 755 College Rd., Princeton NJ, USA#TAB#"],"affiliations":[{"raw_affiliation_string":"Siemens Corporate Research, Image Analytics and Informatics, Princeton, NJ, USA","institution_ids":["https://openalex.org/I4210137693"]},{"raw_affiliation_string":"Siemens Corporate Research-Image Analytics and Informatics, 755 College Rd., Princeton NJ, USA#TAB#","institution_ids":["https://openalex.org/I20089843"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109251531","display_name":"Marie\u2010Pierre Jolly","orcid":null},"institutions":[{"id":"https://openalex.org/I20089843","display_name":"Princeton University","ror":"https://ror.org/00hx57361","country_code":"US","type":"education","lineage":["https://openalex.org/I20089843"]},{"id":"https://openalex.org/I4210137693","display_name":"Siemens (United States)","ror":"https://ror.org/04axb7e79","country_code":"US","type":"company","lineage":["https://openalex.org/I1325886976","https://openalex.org/I4210137693"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Marie-Pierre Jolly","raw_affiliation_strings":["Siemens Corporate Research, Image Analytics and Informatics, Princeton, NJ, USA","Siemens Corporate Research-Image Analytics and Informatics, 755 College Rd., Princeton NJ, USA#TAB#"],"affiliations":[{"raw_affiliation_string":"Siemens Corporate Research, Image Analytics and Informatics, Princeton, NJ, USA","institution_ids":["https://openalex.org/I4210137693"]},{"raw_affiliation_string":"Siemens Corporate Research-Image Analytics and Informatics, 755 College Rd., Princeton NJ, USA#TAB#","institution_ids":["https://openalex.org/I20089843"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016316995","display_name":"Aaron R. Seitz","orcid":"https://orcid.org/0000-0003-4936-9303"},"institutions":[{"id":"https://openalex.org/I103635307","display_name":"University of California, Riverside","ror":"https://ror.org/03nawhv43","country_code":"US","type":"education","lineage":["https://openalex.org/I103635307"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Aaron Seitz","raw_affiliation_strings":["Department of Psychology, University of California Riverside, Riverside, CA, USA","University of California Riverside-Department of Psychology, 900 University Ave., USA"],"affiliations":[{"raw_affiliation_string":"Department of Psychology, University of California Riverside, Riverside, CA, USA","institution_ids":["https://openalex.org/I103635307"]},{"raw_affiliation_string":"University of California Riverside-Department of Psychology, 900 University Ave., USA","institution_ids":["https://openalex.org/I103635307"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5084386176"],"corresponding_institution_ids":["https://openalex.org/I20089843","https://openalex.org/I4210137693"],"apc_list":null,"apc_paid":null,"fwci":2.091,"has_fulltext":false,"cited_by_count":28,"citation_normalized_percentile":{"value":0.89596389,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"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"}},"topics":[{"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"}},{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation 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/T10036","display_name":"Advanced Neural Network Applications","score":0.9986000061035156,"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/segmentation","display_name":"Segmentation","score":0.9208543300628662},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7155210375785828},{"id":"https://openalex.org/keywords/segmentation-based-object-categorization","display_name":"Segmentation-based object categorization","score":0.6782026886940002},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6588724851608276},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.6369152069091797},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.6075756549835205},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5010800361633301},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.48343002796173096},{"id":"https://openalex.org/keywords/minimum-spanning-tree-based-segmentation","display_name":"Minimum spanning tree-based segmentation","score":0.4511982798576355},{"id":"https://openalex.org/keywords/trace","display_name":"TRACE (psycholinguistics)","score":0.4243665635585785},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41769731044769287}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.9208543300628662},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7155210375785828},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.6782026886940002},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6588724851608276},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.6369152069091797},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6075756549835205},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5010800361633301},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.48343002796173096},{"id":"https://openalex.org/C42314347","wikidata":"https://www.wikidata.org/wiki/Q6865488","display_name":"Minimum spanning tree-based segmentation","level":5,"score":0.4511982798576355},{"id":"https://openalex.org/C75291252","wikidata":"https://www.wikidata.org/wiki/Q1315756","display_name":"TRACE (psycholinguistics)","level":2,"score":0.4243665635585785},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41769731044769287},{"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/iccv.2011.6126264","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2011.6126264","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 International Conference on Computer Vision","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.221.4189","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.221.4189","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cns.bu.edu/%7Elgrady/grady2011segmentation.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5099999904632568,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W40954061","https://openalex.org/W1538186882","https://openalex.org/W1967268147","https://openalex.org/W1987983010","https://openalex.org/W1999478155","https://openalex.org/W2025564919","https://openalex.org/W2030644393","https://openalex.org/W2045555777","https://openalex.org/W2056352580","https://openalex.org/W2102627448","https://openalex.org/W2104095591","https://openalex.org/W2112058288","https://openalex.org/W2113089599","https://openalex.org/W2114487471","https://openalex.org/W2115193009","https://openalex.org/W2119300483","https://openalex.org/W2121189958","https://openalex.org/W2121743855","https://openalex.org/W2121927366","https://openalex.org/W2121947440","https://openalex.org/W2124351162","https://openalex.org/W2125637308","https://openalex.org/W2134839354","https://openalex.org/W2138226138","https://openalex.org/W2144950545","https://openalex.org/W2159680539","https://openalex.org/W2160368358","https://openalex.org/W2162310225","https://openalex.org/W2165734775","https://openalex.org/W2169551590","https://openalex.org/W2294819727","https://openalex.org/W2309471314","https://openalex.org/W2533218643","https://openalex.org/W2998023265","https://openalex.org/W3097096317","https://openalex.org/W4234235766","https://openalex.org/W4248635988","https://openalex.org/W6601674298","https://openalex.org/W6683875124"],"related_works":["https://openalex.org/W3144569342","https://openalex.org/W2185902295","https://openalex.org/W2551987074","https://openalex.org/W2945274617","https://openalex.org/W2055202857","https://openalex.org/W2103507220","https://openalex.org/W1543922489","https://openalex.org/W2559983475","https://openalex.org/W2353364291","https://openalex.org/W2531745538"],"abstract_inverted_index":{"Drawing":[0],"a":[1,11,16,28,32,42,48,55,73,83,87,153,158],"box":[2,29,43,56,159],"around":[3],"an":[4],"intended":[5,65],"segmentation":[6,33,50,53,128,155],"target":[7,85,134],"has":[8],"become":[9],"both":[10],"popular":[12],"user":[13],"interface":[14],"and":[15,108,130,150],"common":[17],"output":[18],"for":[19,93],"learning-driven":[20],"detection":[21],"algorithms.":[22],"Despite":[23],"the":[24,39,64,103,111,118,121,127,133,137,140,146,165],"ubiquity":[25],"of":[26,63,75,89,120,126,132],"using":[27],"to":[30,46,81,164],"define":[31,47],"target,":[34],"it":[35],"is":[36,44,57,148],"unclear":[37],"in":[38,86],"literature":[40],"whether":[41,52],"sufficient":[45],"unique":[49],"or":[51],"from":[54,157],"ill-posed":[58],"without":[59],"higher-level":[60],"(semantic)":[61],"knowledge":[62],"target.":[66,167],"We":[67,100],"examine":[68],"this":[69],"issue":[70],"by":[71],"conducting":[72],"study":[74],"14":[76],"subjects":[77,104,138],"who":[78],"are":[79],"asked":[80],"segment":[82],"boxed":[84],"set":[88],"50":[90],"real":[91],"images":[92],"which":[94,160],"they":[95],"have":[96],"no":[97],"semantic":[98],"attachment.":[99],"find":[101],"that":[102,145],"do":[105],"indeed":[106],"perceive":[107],"trace":[109],"almost":[110],"same":[112,141],"segmentations":[113],"as":[114],"each":[115],"other,":[116],"despite":[117],"inhomogeneity":[119],"image":[122],"intensities,":[123],"irregular":[124],"shapes":[125],"targets":[129],"weakness":[131],"boundaries.":[135],"Since":[136],"produce":[139],"segmentation,":[142],"we":[143],"conclude":[144],"problem":[147],"well-posed":[149],"then":[151],"provide":[152],"new":[154],"algorithm":[156],"achieves":[161],"results":[162],"close":[163],"perceived":[166]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":5},{"year":2014,"cited_by_count":2},{"year":2012,"cited_by_count":6}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
