{"id":"https://openalex.org/W7092473117","doi":"https://doi.org/10.1109/tmm.2025.3623529","title":"Efficient Approximation of Earth Mover\u2019s Distance Based on Nearest Neighbor Search","display_name":"Efficient Approximation of Earth Mover\u2019s Distance Based on Nearest Neighbor Search","publication_year":2025,"publication_date":"2025-10-20","ids":{"openalex":"https://openalex.org/W7092473117","doi":"https://doi.org/10.1109/tmm.2025.3623529"},"language":null,"primary_location":{"id":"doi:10.1109/tmm.2025.3623529","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2025.3623529","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"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 Multimedia","raw_type":"journal-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":null,"display_name":"Guangyu Meng","orcid":"https://orcid.org/0000-0003-4825-6542"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Guangyu Meng","raw_affiliation_strings":["Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA"],"raw_orcid":"https://orcid.org/0000-0003-4825-6542","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Ruyu Zhou","orcid":"https://orcid.org/0000-0003-3586-0935"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ruyu Zhou","raw_affiliation_strings":["Department of Applied and Computational Mathematics and Statistics, University of Notre Dame, Notre Dame, IN, USA"],"raw_orcid":"https://orcid.org/0000-0003-3586-0935","affiliations":[{"raw_affiliation_string":"Department of Applied and Computational Mathematics and Statistics, University of Notre Dame, Notre Dame, IN, USA","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Liu Liu","orcid":"https://orcid.org/0000-0003-3307-1596"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Liu Liu","raw_affiliation_strings":["Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA"],"raw_orcid":"https://orcid.org/0000-0003-3307-1596","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Peixian Liang","orcid":null},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Peixian Liang","raw_affiliation_strings":["Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Fang Liu","orcid":"https://orcid.org/0000-0003-3028-5927"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Fang Liu","raw_affiliation_strings":["Department of Applied and Computational Mathematics and Statistics, University of Notre Dame, Notre Dame, IN, USA"],"raw_orcid":"https://orcid.org/0000-0003-3028-5927","affiliations":[{"raw_affiliation_string":"Department of Applied and Computational Mathematics and Statistics, University of Notre Dame, Notre Dame, IN, USA","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Danny Z. Chen","orcid":"https://orcid.org/0000-0001-6565-2884"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Danny Z. Chen","raw_affiliation_strings":["Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA"],"raw_orcid":"https://orcid.org/0000-0001-6565-2884","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Michael Niemier","orcid":"https://orcid.org/0000-0001-7776-4306"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael Niemier","raw_affiliation_strings":["Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA"],"raw_orcid":"https://orcid.org/0000-0001-7776-4306","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"last","author":{"id":null,"display_name":"Xiaobo Sharon Hu","orcid":"https://orcid.org/0000-0002-6636-9738"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaobo Sharon Hu","raw_affiliation_strings":["Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA"],"raw_orcid":"https://orcid.org/0000-0002-6636-9738","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA","institution_ids":["https://openalex.org/I107639228"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.50272981,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"28","issue":null,"first_page":"227","last_page":"240"},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.7940000295639038,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.7940000295639038,"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":0.06539999693632126,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.04010000079870224,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/nearest-neighbor-search","display_name":"Nearest neighbor search","score":0.6657000184059143},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6553000211715698},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.6011000275611877},{"id":"https://openalex.org/keywords/earth-movers-distance","display_name":"Earth mover's distance","score":0.5260000228881836},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5120999813079834},{"id":"https://openalex.org/keywords/vectorization","display_name":"Vectorization (mathematics)","score":0.4221999943256378},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.40529999136924744},{"id":"https://openalex.org/keywords/similarity-measure","display_name":"Similarity measure","score":0.4052000045776367},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.39590001106262207}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8137999773025513},{"id":"https://openalex.org/C116738811","wikidata":"https://www.wikidata.org/wiki/Q608751","display_name":"Nearest neighbor search","level":2,"score":0.6657000184059143},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6553000211715698},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.6011000275611877},{"id":"https://openalex.org/C82668687","wikidata":"https://www.wikidata.org/wiki/Q3046456","display_name":"Earth mover's distance","level":2,"score":0.5260000228881836},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5120999813079834},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.510699987411499},{"id":"https://openalex.org/C41681595","wikidata":"https://www.wikidata.org/wiki/Q7917855","display_name":"Vectorization (mathematics)","level":2,"score":0.4221999943256378},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.40529999136924744},{"id":"https://openalex.org/C2776517306","wikidata":"https://www.wikidata.org/wiki/Q29017317","display_name":"Similarity measure","level":2,"score":0.4052000045776367},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.39590001106262207},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.36890000104904175},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36169999837875366},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35420000553131104},{"id":"https://openalex.org/C2639959","wikidata":"https://www.wikidata.org/wiki/Q1344778","display_name":"Distance measures","level":2,"score":0.336899995803833},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.32170000672340393},{"id":"https://openalex.org/C75165309","wikidata":"https://www.wikidata.org/wiki/Q2258979","display_name":"Search engine indexing","level":2,"score":0.30880001187324524},{"id":"https://openalex.org/C148764684","wikidata":"https://www.wikidata.org/wiki/Q621751","display_name":"Approximation algorithm","level":2,"score":0.3084999918937683},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.30390000343322754},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.3018999993801117},{"id":"https://openalex.org/C161986146","wikidata":"https://www.wikidata.org/wiki/Q4896845","display_name":"Best bin first","level":3,"score":0.2831999957561493},{"id":"https://openalex.org/C125583679","wikidata":"https://www.wikidata.org/wiki/Q755673","display_name":"Search algorithm","level":2,"score":0.2644999921321869},{"id":"https://openalex.org/C21080849","wikidata":"https://www.wikidata.org/wiki/Q13611879","display_name":"Data point","level":2,"score":0.2605000138282776},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.2542000114917755},{"id":"https://openalex.org/C176649486","wikidata":"https://www.wikidata.org/wiki/Q2308807","display_name":"Memory management","level":3,"score":0.25029999017715454}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tmm.2025.3623529","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2025.3623529","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"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 Multimedia","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320332180","display_name":"Defense Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W1493526108","https://openalex.org/W1580389772","https://openalex.org/W1982471090","https://openalex.org/W2007972815","https://openalex.org/W2019106840","https://openalex.org/W2057886711","https://openalex.org/W2061873838","https://openalex.org/W2083258215","https://openalex.org/W2102166818","https://openalex.org/W2104037165","https://openalex.org/W2112796928","https://openalex.org/W2114770744","https://openalex.org/W2125101937","https://openalex.org/W2129112648","https://openalex.org/W2137243801","https://openalex.org/W2141983208","https://openalex.org/W2143668817","https://openalex.org/W2148809531","https://openalex.org/W2161086299","https://openalex.org/W2163380389","https://openalex.org/W2204750386","https://openalex.org/W2222512263","https://openalex.org/W2261553819","https://openalex.org/W2508837377","https://openalex.org/W2530578841","https://openalex.org/W2604721644","https://openalex.org/W2618530766","https://openalex.org/W2740036143","https://openalex.org/W2767009334","https://openalex.org/W2786148476","https://openalex.org/W2914070295","https://openalex.org/W2963694449","https://openalex.org/W2964221667","https://openalex.org/W2997088169","https://openalex.org/W3019140501","https://openalex.org/W3048388568","https://openalex.org/W3165237112","https://openalex.org/W3174868683","https://openalex.org/W3176363435","https://openalex.org/W3188838140","https://openalex.org/W3202127500","https://openalex.org/W4210257365","https://openalex.org/W4210781937","https://openalex.org/W4229740922","https://openalex.org/W4233762729","https://openalex.org/W4239519089","https://openalex.org/W4311459800","https://openalex.org/W4312656438","https://openalex.org/W4387440060","https://openalex.org/W4388824008","https://openalex.org/W4390872578"],"related_works":[],"abstract_inverted_index":{"Earth":[0],"Mover's":[1],"Distance":[2],"(EMD)":[3],"is":[4,26,127],"an":[5],"important":[6],"similarity":[7],"measure":[8],"between":[9,167],"two":[10],"distributions,":[11],"commonly":[12],"used":[13],"in":[14,108,146],"computer":[15],"vision":[16],"and":[17,28,35,56,94,112,141,148,151,163,181,186],"many":[18],"other":[19],"application":[20],"domains.":[21],"However,":[22],"its":[23,33],"exact":[24,69,139,178],"calculation":[25],"computationally":[27],"memory":[29,60,96,187],"intensive,":[30],"which":[31,126],"hinders":[32],"scalability":[34],"applicability":[36],"for":[37,115,130],"large-scale":[38],"problems.":[39],"Various":[40],"approximate":[41,81,143,192],"EMD":[42,82,140,144,179,193],"algorithms":[43,145],"have":[44],"been":[45],"proposed":[46],"to":[47,67,80,159,173,190],"reduce":[48],"computational":[49],"costs,":[50],"but":[51],"they":[52],"suffer":[53],"lower":[54],"accuracy":[55],"may":[57],"require":[58],"additional":[59],"usage":[61],"or":[62],"manual":[63],"parameter":[64],"tuning":[65],"compared":[66,189],"the":[68,102,138,177],"calculation.":[70],"In":[71],"this":[72],"paper,":[73],"we":[74],"present":[75],"a":[76],"novel":[77],"approach,":[78],"NNS-EMD,":[79],"using":[83],"Nearest":[84],"Neighbor":[85],"Search":[86],"(NNS),":[87],"achieving":[88],"high":[89,95],"accuracy,":[90,184],"low":[91],"time":[92],"complexity,":[93],"efficiency.":[97],"The":[98],"NNS":[99,110],"operation":[100],"reduces":[101],"number":[103],"of":[104],"data":[105],"points":[106],"processed":[107],"each":[109],"iteration":[111],"offers":[113,182],"opportunities":[114],"parallel":[116],"processing.":[117],"We":[118,133,155],"further":[119],"accelerate":[120],"NNS-EMD":[121,135,158,169],"via":[122],"vectorization":[123],"on":[124],"GPU,":[125],"especially":[128],"beneficial":[129],"large":[131],"datasets.":[132],"compare":[134],"with":[136],"both":[137],"state-of-the-art":[142],"image":[147,152],"document":[149],"classification":[150],"retrieval":[153],"tasks.":[154],"also":[156],"apply":[157],"calculate":[160],"transport":[161],"mapping":[162],"realize":[164],"color":[165],"transfer":[166],"images.":[168],"achieves":[170],"speed":[171],"44\u00d7":[172],"135\u00d7":[174],"faster":[175],"than":[176],"implementation":[180],"superior":[183],"speedup,":[185],"efficiency":[188],"existing":[191],"methods.":[194]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-21T00:00:00"}