{"id":"https://openalex.org/W2291995163","doi":"https://doi.org/10.1142/s0219467816500042","title":"Sparse Non-Negative Matrix Factorization for Mesh Segmentation","display_name":"Sparse Non-Negative Matrix Factorization for Mesh Segmentation","publication_year":2016,"publication_date":"2016-01-01","ids":{"openalex":"https://openalex.org/W2291995163","doi":"https://doi.org/10.1142/s0219467816500042","mag":"2291995163"},"language":"en","primary_location":{"id":"doi:10.1142/s0219467816500042","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0219467816500042","pdf_url":null,"source":{"id":"https://openalex.org/S60080701","display_name":"International Journal of Image and Graphics","issn_l":"0219-4678","issn":["0219-4678","1793-6756"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Image and Graphics","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":"https://openalex.org/A5090346230","display_name":"Tim McGraw","orcid":"https://orcid.org/0000-0001-6704-6351"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Tim McGraw","raw_affiliation_strings":["Computer Graphics Technology Department, Purdue University, Knoy Hall, West Lafayette, Indiana 47906, USA"],"affiliations":[{"raw_affiliation_string":"Computer Graphics Technology Department, Purdue University, Knoy Hall, West Lafayette, Indiana 47906, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050051792","display_name":"Ji-Sun Kang","orcid":"https://orcid.org/0000-0001-6203-4175"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jisun Kang","raw_affiliation_strings":["Computer Graphics Technology Department, Purdue University, Knoy Hall, West Lafayette, Indiana 47906, USA"],"affiliations":[{"raw_affiliation_string":"Computer Graphics Technology Department, Purdue University, Knoy Hall, West Lafayette, Indiana 47906, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063646349","display_name":"Donald Herring","orcid":null},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Donald Herring","raw_affiliation_strings":["Computer Graphics Technology Department, Purdue University, Knoy Hall, West Lafayette, Indiana 47906, USA"],"affiliations":[{"raw_affiliation_string":"Computer Graphics Technology Department, Purdue University, Knoy Hall, West Lafayette, Indiana 47906, USA","institution_ids":["https://openalex.org/I219193219"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5090346230"],"corresponding_institution_ids":["https://openalex.org/I219193219"],"apc_list":null,"apc_paid":null,"fwci":0.9361,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.72934019,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"16","issue":"01","first_page":"1650004","last_page":"1650004"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9972000122070312,"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/non-negative-matrix-factorization","display_name":"Non-negative matrix factorization","score":0.8566027879714966},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.801421046257019},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6543651819229126},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.647808849811554},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.5951610207557678},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.582795262336731},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5751599669456482},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.5327401757240295},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.46616584062576294},{"id":"https://openalex.org/keywords/sparse-matrix","display_name":"Sparse matrix","score":0.44455063343048096},{"id":"https://openalex.org/keywords/segmentation-based-object-categorization","display_name":"Segmentation-based object categorization","score":0.4336931109428406},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3567963242530823},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.0597720742225647}],"concepts":[{"id":"https://openalex.org/C152671427","wikidata":"https://www.wikidata.org/wiki/Q10843505","display_name":"Non-negative matrix factorization","level":4,"score":0.8566027879714966},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.801421046257019},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6543651819229126},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.647808849811554},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.5951610207557678},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.582795262336731},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5751599669456482},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.5327401757240295},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.46616584062576294},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.44455063343048096},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.4336931109428406},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3567963242530823},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0597720742225647},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","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/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1142/s0219467816500042","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0219467816500042","pdf_url":null,"source":{"id":"https://openalex.org/S60080701","display_name":"International Journal of Image and Graphics","issn_l":"0219-4678","issn":["0219-4678","1793-6756"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Image and Graphics","raw_type":"journal-article"},{"id":"pmh:oai:docs.lib.purdue.edu:cgtpubs-1012","is_oa":false,"landing_page_url":"https://docs.lib.purdue.edu/cgtpubs/13","pdf_url":null,"source":{"id":"https://openalex.org/S4377196310","display_name":"Purdue e-Pubs (Purdue University System)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2801333002","host_organization_name":"Purdue University System","host_organization_lineage":["https://openalex.org/I2801333002"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Computer Graphics Technology Faculty Publications","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W200434350","https://openalex.org/W204135500","https://openalex.org/W1555744841","https://openalex.org/W1590889181","https://openalex.org/W1867620247","https://openalex.org/W1902027874","https://openalex.org/W1976638067","https://openalex.org/W1977556410","https://openalex.org/W1981154266","https://openalex.org/W1986007546","https://openalex.org/W1994393928","https://openalex.org/W1994509172","https://openalex.org/W2013029404","https://openalex.org/W2018122853","https://openalex.org/W2019891074","https://openalex.org/W2023808821","https://openalex.org/W2030797443","https://openalex.org/W2033852356","https://openalex.org/W2050834445","https://openalex.org/W2060280062","https://openalex.org/W2064233581","https://openalex.org/W2075825658","https://openalex.org/W2077678691","https://openalex.org/W2079552990","https://openalex.org/W2082624758","https://openalex.org/W2091715846","https://openalex.org/W2101675075","https://openalex.org/W2116810533","https://openalex.org/W2118718620","https://openalex.org/W2125527601","https://openalex.org/W2132914434","https://openalex.org/W2137390095","https://openalex.org/W2150415460","https://openalex.org/W2151407741","https://openalex.org/W2153663612","https://openalex.org/W2154747411","https://openalex.org/W2158146385","https://openalex.org/W2160167256","https://openalex.org/W2160994953","https://openalex.org/W2165874743","https://openalex.org/W2211252052","https://openalex.org/W2345787032","https://openalex.org/W2347615479","https://openalex.org/W2482276862","https://openalex.org/W2571268788","https://openalex.org/W2999905431","https://openalex.org/W4206225701","https://openalex.org/W4210770595"],"related_works":["https://openalex.org/W2127243424","https://openalex.org/W2037504162","https://openalex.org/W2792706544","https://openalex.org/W1568451138","https://openalex.org/W2539013788","https://openalex.org/W2156699640","https://openalex.org/W2045265907","https://openalex.org/W2972997031","https://openalex.org/W2075222291","https://openalex.org/W2146544734"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"present":[4],"a":[5],"method":[6,64],"for":[7],"3D":[8],"mesh":[9,61,104],"segmentation":[10,85,100],"based":[11,21,86],"on":[12,22,66,75,87],"sparse":[13],"non-negative":[14,45],"matrix":[15,72],"factorization":[16],"(NMF).":[17],"Image":[18],"analysis":[19],"techniques":[20],"NMF":[23,89],"have":[24],"been":[25],"shown":[26],"to":[27,50,92],"decompose":[28],"images":[29,53],"into":[30],"semantically":[31],"meaningful":[32,99],"local":[33],"features.":[34],"Since":[35],"the":[36,47,51,67,76,80,88],"features":[37,48],"and":[38,94],"coefficients":[39],"are":[40],"represented":[41],"in":[42,54,97],"terms":[43],"of":[44,69,79],"values,":[46],"contribute":[49],"resulting":[52],"an":[55,70],"intuitive,":[56],"additive":[57],"fashion.":[58],"Like":[59],"spectral":[60,103],"segmentation,":[62],"our":[63],"relies":[65],"construction":[68],"affinity":[71],"which":[73],"depends":[74],"geometric":[77],"properties":[78],"mesh.":[81],"We":[82],"show":[83],"that":[84],"is":[90],"simpler":[91],"implement,":[93],"can":[95],"result":[96],"more":[98],"results":[101],"than":[102],"segmentation.":[105]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
