{"id":"https://openalex.org/W2153173522","doi":"https://doi.org/10.1109/iccv.2007.4409117","title":"Random Walk and Front Propagation on Watershed Adjacency Graphs for Multilabel Image Segmentation","display_name":"Random Walk and Front Propagation on Watershed Adjacency Graphs for Multilabel Image Segmentation","publication_year":2007,"publication_date":"2007-01-01","ids":{"openalex":"https://openalex.org/W2153173522","doi":"https://doi.org/10.1109/iccv.2007.4409117","mag":"2153173522"},"language":"en","primary_location":{"id":"doi:10.1109/iccv.2007.4409117","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2007.4409117","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 IEEE 11th 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/A5079353895","display_name":"Christophe Chefd\u2019hotel","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"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Christophe Chefd'hotel","raw_affiliation_strings":["Department of Imaging and Visualization, Siemens AG Corporate Research and Development, Princeton, NJ, USA"],"affiliations":[{"raw_affiliation_string":"Department of Imaging and Visualization, Siemens AG Corporate Research and Development, Princeton, NJ, USA","institution_ids":["https://openalex.org/I4210137693"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5097433912","display_name":"Alexis Sebbane","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"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alexis Sebbane","raw_affiliation_strings":["Department of Imaging and Visualization, Siemens AG Corporate Research and Development, Princeton, NJ, USA"],"affiliations":[{"raw_affiliation_string":"Department of Imaging and Visualization, Siemens AG Corporate Research and Development, Princeton, NJ, USA","institution_ids":["https://openalex.org/I4210137693"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5079353895"],"corresponding_institution_ids":["https://openalex.org/I4210137693"],"apc_list":null,"apc_paid":null,"fwci":0.9737,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.79414775,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9997000098228455,"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":0.9997000098228455,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9997000098228455,"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":0.9983000159263611,"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/adjacency-list","display_name":"Adjacency list","score":0.7598681449890137},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6425430774688721},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5694631338119507},{"id":"https://openalex.org/keywords/watershed","display_name":"Watershed","score":0.5563268661499023},{"id":"https://openalex.org/keywords/spurious-relationship","display_name":"Spurious relationship","score":0.5349074602127075},{"id":"https://openalex.org/keywords/geodesic","display_name":"Geodesic","score":0.5316264033317566},{"id":"https://openalex.org/keywords/maxima-and-minima","display_name":"Maxima and minima","score":0.4707655906677246},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4416019916534424},{"id":"https://openalex.org/keywords/graph-partition","display_name":"Graph partition","score":0.43103259801864624},{"id":"https://openalex.org/keywords/adjacency-matrix","display_name":"Adjacency matrix","score":0.4281647503376007},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.42612335085868835},{"id":"https://openalex.org/keywords/partition","display_name":"Partition (number theory)","score":0.4257262349128723},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.37815406918525696},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.37348389625549316},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.31265750527381897},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.30413734912872314},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.2427385151386261},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.13136830925941467},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.11430677771568298}],"concepts":[{"id":"https://openalex.org/C110484373","wikidata":"https://www.wikidata.org/wiki/Q264398","display_name":"Adjacency list","level":2,"score":0.7598681449890137},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6425430774688721},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5694631338119507},{"id":"https://openalex.org/C150547873","wikidata":"https://www.wikidata.org/wiki/Q947851","display_name":"Watershed","level":2,"score":0.5563268661499023},{"id":"https://openalex.org/C97256817","wikidata":"https://www.wikidata.org/wiki/Q1462316","display_name":"Spurious relationship","level":2,"score":0.5349074602127075},{"id":"https://openalex.org/C165818556","wikidata":"https://www.wikidata.org/wiki/Q213488","display_name":"Geodesic","level":2,"score":0.5316264033317566},{"id":"https://openalex.org/C186633575","wikidata":"https://www.wikidata.org/wiki/Q845060","display_name":"Maxima and minima","level":2,"score":0.4707655906677246},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4416019916534424},{"id":"https://openalex.org/C48903430","wikidata":"https://www.wikidata.org/wiki/Q491370","display_name":"Graph partition","level":3,"score":0.43103259801864624},{"id":"https://openalex.org/C180356752","wikidata":"https://www.wikidata.org/wiki/Q727035","display_name":"Adjacency matrix","level":3,"score":0.4281647503376007},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.42612335085868835},{"id":"https://openalex.org/C42812","wikidata":"https://www.wikidata.org/wiki/Q1082910","display_name":"Partition (number theory)","level":2,"score":0.4257262349128723},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.37815406918525696},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37348389625549316},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.31265750527381897},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.30413734912872314},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2427385151386261},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.13136830925941467},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.11430677771568298},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccv.2007.4409117","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2007.4409117","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 IEEE 11th International Conference on Computer Vision","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/15","score":0.75,"display_name":"Life in Land"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1562474711","https://openalex.org/W1599786999","https://openalex.org/W1652775531","https://openalex.org/W1709754610","https://openalex.org/W1987983010","https://openalex.org/W1995714461","https://openalex.org/W2030088149","https://openalex.org/W2049391017","https://openalex.org/W2063266501","https://openalex.org/W2091595991","https://openalex.org/W2103148294","https://openalex.org/W2118858457","https://openalex.org/W2120963736","https://openalex.org/W2121947440","https://openalex.org/W2124260943","https://openalex.org/W2125637308","https://openalex.org/W2127731579","https://openalex.org/W2129872026","https://openalex.org/W2169551590","https://openalex.org/W2294819727","https://openalex.org/W2798909945","https://openalex.org/W4234235766"],"related_works":["https://openalex.org/W4213150077","https://openalex.org/W2369410163","https://openalex.org/W2059018062","https://openalex.org/W2078477160","https://openalex.org/W1989103179","https://openalex.org/W1991172810","https://openalex.org/W125803343","https://openalex.org/W2117632582","https://openalex.org/W4388347373","https://openalex.org/W2604585036"],"abstract_inverted_index":{"The":[0],"watershed":[1,40,76,140],"partition":[2,83,114],"of":[3,17,50,74,115,157],"an":[4,95],"image":[5,33,136],"often":[6],"results":[7],"in":[8,31],"over-segmentation.":[9],"This":[10],"well-known":[11],"phenomenon":[12],"is":[13,42,84],"due":[14],"to":[15,23,45,60,70],"variations":[16],"intensity":[18],"that":[19,89],"do":[20],"not":[21],"correspond":[22],"object":[24],"boundaries":[25],"and":[26,148,155,165],"produce":[27],"spurious":[28],"local":[29],"minima":[30,37],"the":[32,51,71,75,82,87,107,116,153],"gradient":[34],"magnitude.":[35],"Filtering":[36],"or":[38],"merging":[39],"regions":[41],"then":[43],"necessary":[44],"obtain":[46],"a":[47,90,100,103,112,139],"higher-level":[48],"description":[49],"data.":[52],"In":[53,78,106],"this":[54,61,158],"paper,":[55],"we":[56,110],"propose":[57],"new":[58],"solutions":[59],"problem":[62],"by":[63],"applying":[64],"two":[65],"interactive":[66],"multilabel":[67],"partitioning":[68],"techniques":[69,132],"adjacency":[72,141],"graph":[73,117,142],"regions.":[77],"our":[79],"first":[80,98],"approach,":[81,109],"derived":[85],"from":[86],"probability":[88],"\"random":[91],"walker\"":[92],"starting":[93,121],"at":[94,122],"arbitrary":[96],"node,":[97],"reaches":[99],"node":[101],"with":[102,160],"pre-assigned":[104],"label.":[105],"second":[108],"compute":[111],"geodesic":[113],"using":[118],"competing":[119],"wavefronts":[120],"prescribed":[123],"nodes.":[124],"Both":[125],"methods":[126],"are":[127],"based":[128],"on":[129,135,163],"existing":[130],"segmentation":[131],"previously":[133],"implemented":[134],"lattices.":[137],"Using":[138],"greatly":[143],"reduces":[144],"their":[145],"memory":[146],"footprint":[147],"computational":[149],"cost.":[150],"We":[151],"demonstrate":[152],"practicality":[154],"versatility":[156],"approach":[159],"several":[161],"experiments":[162],"2D":[164],"3D":[166],"datasets.":[167]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2015,"cited_by_count":1},{"year":2012,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
