{"id":"https://openalex.org/W2134737484","doi":"https://doi.org/10.1109/cvprw.2010.5543585","title":"Structural correspondence as a contour grouping problem","display_name":"Structural correspondence as a contour grouping problem","publication_year":2010,"publication_date":"2010-06-01","ids":{"openalex":"https://openalex.org/W2134737484","doi":"https://doi.org/10.1109/cvprw.2010.5543585","mag":"2134737484"},"language":"en","primary_location":{"id":"doi:10.1109/cvprw.2010.5543585","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvprw.2010.5543585","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops","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/A5007807315","display_name":"Elena Bernardis","orcid":"https://orcid.org/0000-0002-5558-8695"},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Elena Bernardis","raw_affiliation_strings":["University of Pennsylvania, Philadelphia, PA, USA","University of Pennsylvania, Philadelphia, 19104 USA"],"affiliations":[{"raw_affiliation_string":"University of Pennsylvania, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I79576946"]},{"raw_affiliation_string":"University of Pennsylvania, Philadelphia, 19104 USA","institution_ids":["https://openalex.org/I79576946"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042014034","display_name":"Stella X. Yu","orcid":"https://orcid.org/0000-0002-3507-5761"},"institutions":[{"id":"https://openalex.org/I103531236","display_name":"Boston College","ror":"https://ror.org/02n2fzt79","country_code":"US","type":"education","lineage":["https://openalex.org/I103531236"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Stella X. Yu","raw_affiliation_strings":["Boston College Graduate School, Chestnut Hill, MA, USA","Boston College; Chestnut Hill MA 02467 USA"],"affiliations":[{"raw_affiliation_string":"Boston College Graduate School, Chestnut Hill, MA, USA","institution_ids":["https://openalex.org/I103531236"]},{"raw_affiliation_string":"Boston College; Chestnut Hill MA 02467 USA","institution_ids":["https://openalex.org/I103531236"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5007807315"],"corresponding_institution_ids":["https://openalex.org/I79576946"],"apc_list":null,"apc_paid":null,"fwci":0.3233,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.63429401,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"194","last_page":"199"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation 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/T10052","display_name":"Medical Image Segmentation 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/T12923","display_name":"Digital Image Processing Techniques","score":0.9979000091552734,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9975000023841858,"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/salient","display_name":"Salient","score":0.8244491219520569},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5842273831367493},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5447427034378052},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5372151732444763},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.49870800971984863},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.47105666995048523},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4569675028324127},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.4543946087360382},{"id":"https://openalex.org/keywords/spectral-space","display_name":"Spectral space","score":0.4376157820224762},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.42378634214401245},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.33956581354141235},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.1245681643486023},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07983329892158508}],"concepts":[{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.8244491219520569},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5842273831367493},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5447427034378052},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5372151732444763},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.49870800971984863},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.47105666995048523},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4569675028324127},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.4543946087360382},{"id":"https://openalex.org/C2778740170","wikidata":"https://www.wikidata.org/wiki/Q7575210","display_name":"Spectral space","level":2,"score":0.4376157820224762},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.42378634214401245},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33956581354141235},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.1245681643486023},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07983329892158508},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/cvprw.2010.5543585","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvprw.2010.5543585","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.175.1445","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.175.1445","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.seas.upenn.edu/%7Eelber/paperi/tubes_mmbia2010.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320309370","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10"},{"id":"https://openalex.org/F4320309622","display_name":"Harvard University","ror":"https://ror.org/03vek6s52"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1830094849","https://openalex.org/W1978627835","https://openalex.org/W1991113069","https://openalex.org/W2019072823","https://openalex.org/W2025818287","https://openalex.org/W2121947440","https://openalex.org/W2132603077","https://openalex.org/W2134002877","https://openalex.org/W2160411867","https://openalex.org/W3100816363","https://openalex.org/W6677945368"],"related_works":["https://openalex.org/W2329500892","https://openalex.org/W28991112","https://openalex.org/W2370726991","https://openalex.org/W2369710579","https://openalex.org/W4327728159","https://openalex.org/W4394266730","https://openalex.org/W1990856605","https://openalex.org/W2053783616","https://openalex.org/W2545348020","https://openalex.org/W2293263892"],"abstract_inverted_index":{"We":[0,32],"present":[1],"a":[2,20,54,83],"novel":[3],"viewpoint":[4],"which":[5,98],"approaches":[6],"the":[7,15,48,59,62,75,86,110],"structural":[8],"correspondence":[9],"across":[10],"an":[11],"image":[12],"stack":[13],"in":[14,38,47,58,91],"3D":[16,25,49,56,100],"space":[17,60],"as":[18],"solving":[19],"contour":[21,80,87],"grouping":[22,34],"problem.":[23],"Finding":[24],"cellular":[26],"tubes":[27,101],"becomes":[28],"finding":[29],"closed":[30],"contours.":[31],"derive":[33],"cues":[35],"between":[36],"cells":[37],"adjacent":[39],"slices":[40],"based":[41],"on":[42],"their":[43],"ability":[44],"to":[45],"relate":[46],"space.":[50],"Those":[51],"that":[52],"form":[53],"long":[55],"tube":[57],"become":[61,71],"most":[63],"salient":[64],"contour,":[65],"while":[66],"those":[67],"of":[68,94,102],"shorter":[69],"lengths":[70,104],"less":[72],"salient.":[73],"In":[74],"spectral":[76],"graph-theoretical":[77],"framework":[78],"for":[79,112],"grouping,":[81],"such":[82],"separation":[84],"by":[85],"length":[88],"is":[89],"reflected":[90],"complex":[92],"eigenvectors":[93],"different":[95],"magnitudes,":[96],"from":[97],"these":[99],"varying":[103],"can":[105],"thus":[106],"be":[107],"extracted,":[108],"obviating":[109],"need":[111],"identifying":[113],"missing":[114],"correspondences.":[115]},"counts_by_year":[{"year":2012,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
