{"id":"https://openalex.org/W1585978503","doi":"https://doi.org/10.1109/tip.2015.2449552","title":"Multiscale Superpixels and Supervoxels Based on Hierarchical Edge-Weighted Centroidal Voronoi Tessellation","display_name":"Multiscale Superpixels and Supervoxels Based on Hierarchical Edge-Weighted Centroidal Voronoi Tessellation","publication_year":2015,"publication_date":"2015-07-22","ids":{"openalex":"https://openalex.org/W1585978503","doi":"https://doi.org/10.1109/tip.2015.2449552","mag":"1585978503","pmid":"https://pubmed.ncbi.nlm.nih.gov/26111396"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2015.2449552","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2015.2449552","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5102993434","display_name":"Youjie Zhou","orcid":"https://orcid.org/0000-0001-7188-6329"},"institutions":[{"id":"https://openalex.org/I155781252","display_name":"University of South Carolina","ror":"https://ror.org/02b6qw903","country_code":"US","type":"education","lineage":["https://openalex.org/I155781252"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Youjie Zhou","raw_affiliation_strings":["Department of Computer Science and Engineering, University of South Carolina, Columbia, SC, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of South Carolina, Columbia, SC, USA","institution_ids":["https://openalex.org/I155781252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076382628","display_name":"Lili Ju","orcid":"https://orcid.org/0000-0002-6520-582X"},"institutions":[{"id":"https://openalex.org/I155781252","display_name":"University of South Carolina","ror":"https://ror.org/02b6qw903","country_code":"US","type":"education","lineage":["https://openalex.org/I155781252"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lili Ju","raw_affiliation_strings":["Department of Mathematics, University of South Carolina, Columbia, SC, USA","Department of Mathematics, University of South Carolina, Columbia, SC, USA#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, University of South Carolina, Columbia, SC, USA","institution_ids":["https://openalex.org/I155781252"]},{"raw_affiliation_string":"Department of Mathematics, University of South Carolina, Columbia, SC, USA#TAB#","institution_ids":["https://openalex.org/I155781252"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082259804","display_name":"Song Wang","orcid":"https://orcid.org/0000-0003-4152-5295"},"institutions":[{"id":"https://openalex.org/I155781252","display_name":"University of South Carolina","ror":"https://ror.org/02b6qw903","country_code":"US","type":"education","lineage":["https://openalex.org/I155781252"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Song Wang","raw_affiliation_strings":["Department of Computer Science and Engineering, University of South Carolina, Columbia, SC, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of South Carolina, Columbia, SC, USA","institution_ids":["https://openalex.org/I155781252"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I155781252"],"apc_list":null,"apc_paid":null,"fwci":1.8367,"has_fulltext":false,"cited_by_count":30,"citation_normalized_percentile":{"value":0.89942567,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"24","issue":"11","first_page":"3834","last_page":"3845"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9977999925613403,"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":0.9977999925613403,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9934999942779541,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9713000059127808,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.8166704177856445},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7080063819885254},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.687916100025177},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5671634674072266},{"id":"https://openalex.org/keywords/centroidal-voronoi-tessellation","display_name":"Centroidal Voronoi tessellation","score":0.5629129409790039},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5519178509712219},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5395826697349548},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5372699499130249},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.45000624656677246},{"id":"https://openalex.org/keywords/voxel","display_name":"Voxel","score":0.43410563468933105},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4125913977622986},{"id":"https://openalex.org/keywords/voronoi-diagram","display_name":"Voronoi diagram","score":0.28689801692962646},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.23535871505737305}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8166704177856445},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7080063819885254},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.687916100025177},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5671634674072266},{"id":"https://openalex.org/C205672865","wikidata":"https://www.wikidata.org/wiki/Q5062961","display_name":"Centroidal Voronoi tessellation","level":3,"score":0.5629129409790039},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5519178509712219},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5395826697349548},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5372699499130249},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.45000624656677246},{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.43410563468933105},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4125913977622986},{"id":"https://openalex.org/C24881265","wikidata":"https://www.wikidata.org/wiki/Q757267","display_name":"Voronoi diagram","level":2,"score":0.28689801692962646},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23535871505737305},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2015.2449552","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2015.2449552","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},{"id":"pmid:26111396","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/26111396","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on image processing : a publication of the IEEE Signal Processing Society","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.8600000143051147}],"awards":[{"id":"https://openalex.org/G3165732353","display_name":null,"funder_award_id":"FA9550-11-1-0327","funder_id":"https://openalex.org/F4320338279","funder_display_name":"Air Force Office of Scientific Research"},{"id":"https://openalex.org/G7226084225","display_name":null,"funder_award_id":"IIS-1017199","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320338279","display_name":"Air Force Office of Scientific Research","ror":"https://ror.org/011e9bt93"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W159595522","https://openalex.org/W1508404128","https://openalex.org/W1542770311","https://openalex.org/W1548953334","https://openalex.org/W1578197944","https://openalex.org/W1955404912","https://openalex.org/W2010975286","https://openalex.org/W2017313218","https://openalex.org/W2026806415","https://openalex.org/W2030346542","https://openalex.org/W2051752778","https://openalex.org/W2054279472","https://openalex.org/W2060004468","https://openalex.org/W2061202859","https://openalex.org/W2067191022","https://openalex.org/W2070232376","https://openalex.org/W2081314642","https://openalex.org/W2081432165","https://openalex.org/W2104125540","https://openalex.org/W2105960416","https://openalex.org/W2108424265","https://openalex.org/W2116877738","https://openalex.org/W2118246710","https://openalex.org/W2119531662","https://openalex.org/W2121927366","https://openalex.org/W2125378844","https://openalex.org/W2133141088","https://openalex.org/W2139086308","https://openalex.org/W2165133955","https://openalex.org/W2294602567","https://openalex.org/W3152156909","https://openalex.org/W4285719527","https://openalex.org/W6606481039","https://openalex.org/W6630399218","https://openalex.org/W6632792525","https://openalex.org/W6634886587","https://openalex.org/W6653423199","https://openalex.org/W6670927870","https://openalex.org/W6697111280"],"related_works":["https://openalex.org/W2059217232","https://openalex.org/W2371724110","https://openalex.org/W2606237981","https://openalex.org/W3027020613","https://openalex.org/W1992160534","https://openalex.org/W2016533837","https://openalex.org/W2731434452","https://openalex.org/W637922621","https://openalex.org/W3167885074","https://openalex.org/W2892386716"],"abstract_inverted_index":{"Superpixels":[0],"and":[1,18,87,128,141,147],"supervoxels":[2],"play":[3],"an":[4],"important":[5],"role":[6],"in":[7,38,54,64],"many":[8],"computer":[9],"vision":[10],"applications,":[11],"such":[12],"as":[13,48],"image":[14,140],"segmentation,":[15],"object":[16],"recognition,":[17],"video":[19,142],"analysis.":[20],"In":[21,41,68],"this":[22,42],"paper,":[23],"we":[24,44,126],"propose":[25],"a":[26,49,100],"new":[27],"hierarchical":[28,101],"edge-weighted":[29],"centroidal":[30],"Voronoi":[31],"tessellation":[32],"(HEWCVT)":[33],"method":[34,132,155],"for":[35],"generating":[36],"superpixels/supervoxels":[37,53,63,94,109,120],"multiple":[39],"scales.":[40,112],"method,":[43],"model":[45],"the":[46,65,69,72,105,116,130,152],"problem":[47],"multilevel":[50],"clustering":[51,74,81],"process:":[52],"one":[55],"level":[56],"are":[57],"clustered":[58],"to":[59],"obtain":[60],"larger":[61],"size":[62],"next":[66],"level.":[67],"finest":[70],"scale,":[71],"initial":[73],"is":[75],"directly":[76],"conducted":[77],"on":[78,138],"pixels/voxels.":[79],"The":[80,92],"energy":[82],"involves":[83],"both":[84],"color":[85],"similarities":[86],"boundary":[88],"smoothness":[89],"of":[90,108,118],"superpixels/supervoxels.":[91],"resulting":[93],"can":[95],"be":[96],"easily":[97],"represented":[98],"by":[99],"tree":[102],"which":[103],"describes":[104],"nesting":[106],"relation":[107],"across":[110],"different":[111,122],"We":[113],"first":[114],"investigate":[115],"performance":[117],"obtained":[119],"under":[121],"parameter":[123],"settings,":[124],"then":[125],"evaluate":[127],"compare":[129],"proposed":[131,153],"with":[133,161],"several":[134],"state-of-the-art":[135],"superpixel/supervoxel":[136],"methods":[137],"standard":[139],"data":[143],"sets.":[144],"Both":[145],"quantitative":[146],"qualitative":[148],"results":[149],"show":[150],"that":[151],"HEWCVT":[154],"achieves":[156],"superior":[157],"or":[158],"comparable":[159],"performances":[160],"other":[162],"methods.":[163]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
