{"id":"https://openalex.org/W2514783721","doi":"https://doi.org/10.1109/icme.2016.7552867","title":"Robust image matching via feature guided Gaussian mixture model","display_name":"Robust image matching via feature guided Gaussian mixture model","publication_year":2016,"publication_date":"2016-07-01","ids":{"openalex":"https://openalex.org/W2514783721","doi":"https://doi.org/10.1109/icme.2016.7552867","mag":"2514783721"},"language":"en","primary_location":{"id":"doi:10.1109/icme.2016.7552867","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme.2016.7552867","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Multimedia and Expo (ICME)","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/A5040010053","display_name":"Jiayi Ma","orcid":"https://orcid.org/0000-0003-3264-3265"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiayi Ma","raw_affiliation_strings":["Electronic Information School, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Electronic Information School, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087165831","display_name":"Junjun Jiang","orcid":"https://orcid.org/0000-0002-5694-505X"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junjun Jiang","raw_affiliation_strings":["School of Computer Science, China University of Geosciences, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101909196","display_name":"Yuan Gao","orcid":"https://orcid.org/0000-0002-7661-2367"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Yuan Gao","raw_affiliation_strings":["Department of Electronic Engineering, City University of Hong Kong, Hong Kong"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, City University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004753222","display_name":"Jun Chen","orcid":"https://orcid.org/0000-0001-9005-6849"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Chen","raw_affiliation_strings":["School of Automation, China University of Geosciences, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Automation, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101429593","display_name":"Chengyin Liu","orcid":"https://orcid.org/0000-0002-4816-152X"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chengyin Liu","raw_affiliation_strings":["Electronic Information School, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Electronic Information School, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5040010053"],"corresponding_institution_ids":["https://openalex.org/I37461747"],"apc_list":null,"apc_paid":null,"fwci":0.835,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.80551127,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval 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/T10627","display_name":"Advanced Image and Video Retrieval 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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9958000183105469,"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":0.9922999739646912,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6840568780899048},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.668075680732727},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6177504658699036},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6087201237678528},{"id":"https://openalex.org/keywords/expectation\u2013maximization-algorithm","display_name":"Expectation\u2013maximization algorithm","score":0.5688481330871582},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.556943953037262},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5184585452079773},{"id":"https://openalex.org/keywords/point-set-registration","display_name":"Point set registration","score":0.5164787769317627},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.49028781056404114},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.46567413210868835},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.458290696144104},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.43654438853263855},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.4339887499809265},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.43280866742134094},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.28284651041030884},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.13454487919807434}],"concepts":[{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6840568780899048},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.668075680732727},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6177504658699036},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6087201237678528},{"id":"https://openalex.org/C182081679","wikidata":"https://www.wikidata.org/wiki/Q1275153","display_name":"Expectation\u2013maximization algorithm","level":3,"score":0.5688481330871582},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.556943953037262},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5184585452079773},{"id":"https://openalex.org/C200336642","wikidata":"https://www.wikidata.org/wiki/Q15058706","display_name":"Point set registration","level":3,"score":0.5164787769317627},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.49028781056404114},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.46567413210868835},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.458290696144104},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.43654438853263855},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4339887499809265},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.43280866742134094},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.28284651041030884},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.13454487919807434},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","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},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icme.2016.7552867","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme.2016.7552867","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W59289346","https://openalex.org/W1663973292","https://openalex.org/W1950038212","https://openalex.org/W1980911747","https://openalex.org/W1986280275","https://openalex.org/W2001881245","https://openalex.org/W2028683638","https://openalex.org/W2046434485","https://openalex.org/W2049981393","https://openalex.org/W2066941820","https://openalex.org/W2070789837","https://openalex.org/W2071730188","https://openalex.org/W2085261163","https://openalex.org/W2088374681","https://openalex.org/W2088777113","https://openalex.org/W2097089247","https://openalex.org/W2101563584","https://openalex.org/W2106199912","https://openalex.org/W2114354851","https://openalex.org/W2115003579","https://openalex.org/W2119305944","https://openalex.org/W2120501941","https://openalex.org/W2124141313","https://openalex.org/W2130871783","https://openalex.org/W2134236847","https://openalex.org/W2137089267","https://openalex.org/W2150190641","https://openalex.org/W2151103935","https://openalex.org/W2157656099","https://openalex.org/W2169633581","https://openalex.org/W2171490473","https://openalex.org/W4212863985","https://openalex.org/W6997266731"],"related_works":["https://openalex.org/W2473373438","https://openalex.org/W2368486525","https://openalex.org/W2077224612","https://openalex.org/W2075383893","https://openalex.org/W84255947","https://openalex.org/W2153481672","https://openalex.org/W4312864369","https://openalex.org/W2014842417","https://openalex.org/W2891133681","https://openalex.org/W2061347451"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"propose":[4],"a":[5,37,43,77,101,107,114],"novel":[6],"feature":[7,23,38,93],"guided":[8,39],"Gaussian":[9,61],"mixture":[10,40],"model":[11],"(FG-GMM)":[12],"for":[13],"image":[14,96],"matching,":[15],"which":[16,129],"typically":[17],"requires":[18],"matching":[19],"two":[20],"sets":[21],"of":[22,36,41,59,126],"points":[24],"extracted":[25],"from":[26],"the":[27,32,54,60,68,91,124],"given":[28],"images.":[29],"We":[30],"formulate":[31],"problem":[33,73],"as":[34],"estimation":[35],"densities:":[42],"GMM":[44],"is":[45,74,98,110],"fitted":[46],"to":[47,65,112],"one":[48],"point":[49,70],"set,":[50],"such":[51],"that":[52],"both":[53],"centers":[55],"and":[56,106],"local":[57],"features":[58],"densities":[62],"are":[63],"constrained":[64],"coincide":[66],"with":[67,82],"other":[69,132],"set.":[71],"The":[72,95],"solved":[75],"under":[76],"unified":[78],"maximum-likelihood":[79],"framework":[80],"together":[81],"an":[83],"iterative":[84],"semi-supervised":[85],"Expectation-Maximization":[86],"(EM)":[87],"algorithm":[88],"initialized":[89],"by":[90],"confident":[92],"correspondences.":[94],"transformation":[97],"specified":[99],"in":[100],"reproducing":[102],"kernel":[103],"Hilbert":[104],"space":[105],"sparse":[108],"approximation":[109],"adopted":[111],"achieve":[113],"fast":[115],"implementation.":[116],"Extensive":[117],"experiments":[118],"on":[119],"various":[120],"real":[121],"images":[122],"show":[123],"robustness":[125],"our":[127],"approach,":[128],"consistently":[130],"outperforms":[131],"state-of-the-art":[133],"methods.":[134]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2017,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}