{"id":"https://openalex.org/W2139786691","doi":"https://doi.org/10.1109/cvpr.2003.1211337","title":"A variational framework for image segmentation combining motion estimation and shape regularization","display_name":"A variational framework for image segmentation combining motion estimation and shape regularization","publication_year":2003,"publication_date":"2003-11-21","ids":{"openalex":"https://openalex.org/W2139786691","doi":"https://doi.org/10.1109/cvpr.2003.1211337","mag":"2139786691"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2003.1211337","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2003.1211337","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings.","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/A5087710605","display_name":"Daniel Cremers","orcid":"https://orcid.org/0000-0002-3079-7984"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"D. Cremers","raw_affiliation_strings":["Department of Computer Science, University of California, Los Angeles, CA, USA","Department of Computer Science, University of California, Los Angeles , CA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of California, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I161318765"]},{"raw_affiliation_string":"Department of Computer Science, University of California, Los Angeles , CA, USA","institution_ids":["https://openalex.org/I161318765"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5087710605"],"corresponding_institution_ids":["https://openalex.org/I161318765"],"apc_list":null,"apc_paid":null,"fwci":6.7295,"has_fulltext":false,"cited_by_count":54,"citation_normalized_percentile":{"value":0.97269661,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"18","issue":null,"first_page":"I","last_page":"53"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","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"}},"topics":[{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","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/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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9962000250816345,"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/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.6693221926689148},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6692451238632202},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.6610682606697083},{"id":"https://openalex.org/keywords/segmentation-based-object-categorization","display_name":"Segmentation-based object categorization","score":0.6325521469116211},{"id":"https://openalex.org/keywords/motion-estimation","display_name":"Motion estimation","score":0.6229863166809082},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6030922532081604},{"id":"https://openalex.org/keywords/energy-functional","display_name":"Energy functional","score":0.5877508521080017},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5591997504234314},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5360335111618042},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4951755106449127},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.45656120777130127},{"id":"https://openalex.org/keywords/optical-flow","display_name":"Optical flow","score":0.4334191083908081},{"id":"https://openalex.org/keywords/motion-field","display_name":"Motion field","score":0.4281124472618103},{"id":"https://openalex.org/keywords/boundary","display_name":"Boundary (topology)","score":0.4158411920070648},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39513352513313293},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.31275010108947754},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.13308191299438477}],"concepts":[{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.6693221926689148},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6692451238632202},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6610682606697083},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.6325521469116211},{"id":"https://openalex.org/C10161872","wikidata":"https://www.wikidata.org/wiki/Q557891","display_name":"Motion estimation","level":2,"score":0.6229863166809082},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6030922532081604},{"id":"https://openalex.org/C191640071","wikidata":"https://www.wikidata.org/wiki/Q5377056","display_name":"Energy functional","level":2,"score":0.5877508521080017},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5591997504234314},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5360335111618042},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4951755106449127},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.45656120777130127},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.4334191083908081},{"id":"https://openalex.org/C124774092","wikidata":"https://www.wikidata.org/wiki/Q6917782","display_name":"Motion field","level":3,"score":0.4281124472618103},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.4158411920070648},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39513352513313293},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.31275010108947754},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.13308191299438477}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/cvpr.2003.1211337","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2003.1211337","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings.","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.364.4863","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.364.4863","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://vision.in.tum.de/_media/spezial/bib/cvpr03.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.8.329","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.8.329","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.vision.cs.ucla.edu/papers/cremers-cvpr03.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.6499999761581421}],"awards":[],"funders":[{"id":"https://openalex.org/F4320337345","display_name":"Office of Naval Research","ror":"https://ror.org/00rk2pe57"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W157025503","https://openalex.org/W190374205","https://openalex.org/W1506879382","https://openalex.org/W1556481352","https://openalex.org/W1572544957","https://openalex.org/W1578285471","https://openalex.org/W1961031432","https://openalex.org/W1965282187","https://openalex.org/W2062396579","https://openalex.org/W2098152234","https://openalex.org/W2100315781","https://openalex.org/W2114487471","https://openalex.org/W2116040950","https://openalex.org/W2127986149","https://openalex.org/W2138524633","https://openalex.org/W2151158672","https://openalex.org/W2156177012","https://openalex.org/W2751023760"],"related_works":["https://openalex.org/W1501297619","https://openalex.org/W2354637046","https://openalex.org/W2120943489","https://openalex.org/W1484667368","https://openalex.org/W4286646204","https://openalex.org/W1988727984","https://openalex.org/W2093488518","https://openalex.org/W2130582613","https://openalex.org/W2030154815","https://openalex.org/W2051121715"],"abstract_inverted_index":{"Based":[0],"on":[1,16,56,74],"a":[2,13,24,78,83,107],"geometric":[3],"interpretation":[4],"of":[5,30,36,67,80,96,121,129],"the":[6,17,28,31,44,57,94,122,125],"optic":[7],"flow":[8],"constraint":[9],"equation,":[10],"we":[11],"propose":[12],"conditional":[14],"probability":[15],"spatio-temporal":[18,58],"image":[19,32,59,69],"gradient.":[20],"We":[21],"consistently":[22],"derive":[23],"variational":[25],"approach":[26],"for":[27,77],"segmentation":[29,50,101],"domain":[33],"into":[34],"regions":[35,81],"homogeneous":[37],"motion.":[38],"The":[39],"proposed":[40],"energy":[41],"functional":[42,46],"extends":[43],"Mumford-Shah":[45],"from":[47,62],"gray":[48],"value":[49],"to":[51,90],"motion":[52,75,97,100],"segmentation.":[53],"It":[54],"depends":[55,73],"gradient":[60],"calculated":[61],"only":[63],"two":[64],"consecutive":[65],"images":[66],"an":[68],"sequence.":[70],"Moreover,":[71],"it":[72],"vectors":[76],"set":[79,118],"and":[82,99,115,127],"boundary":[84,123],"separating":[85],"these":[86],"regions.":[87],"In":[88],"contrast":[89],"most":[91],"alternative":[92],"approaches,":[93],"problems":[95],"estimation":[98],"are":[102],"jointly":[103],"solved":[104],"by":[105],"minimizing":[106],"single":[108],"functional.":[109],"Numerical":[110],"evaluation":[111],"with":[112],"both":[113],"explicit":[114],"implicit":[116],"(level":[117],"based)":[119],"representations":[120],"shows":[124],"strengths":[126],"limitations":[128],"our":[130],"approach.":[131]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":2},{"year":2012,"cited_by_count":2}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}