{"id":"https://openalex.org/W2200042254","doi":"https://doi.org/10.1109/clei.2015.7359459","title":"Efficient approach for interest points detection in non-rigid shapes","display_name":"Efficient approach for interest points detection in non-rigid shapes","publication_year":2015,"publication_date":"2015-10-01","ids":{"openalex":"https://openalex.org/W2200042254","doi":"https://doi.org/10.1109/clei.2015.7359459","mag":"2200042254"},"language":"en","primary_location":{"id":"doi:10.1109/clei.2015.7359459","is_oa":false,"landing_page_url":"https://doi.org/10.1109/clei.2015.7359459","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 Latin American Computing Conference (CLEI)","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/A5012304998","display_name":"Cristian Lopez","orcid":"https://orcid.org/0000-0002-2568-650X"},"institutions":[{"id":"https://openalex.org/I120753068","display_name":"Universidad La Salle","ror":"https://ror.org/05sr4vg14","country_code":"BO","type":"education","lineage":["https://openalex.org/I120753068"]}],"countries":["BO"],"is_corresponding":true,"raw_author_name":"Cristian Jose Lopez Del Alamo","raw_affiliation_strings":["Universidad La Salle, Arequipa, Per\u00fa"],"affiliations":[{"raw_affiliation_string":"Universidad La Salle, Arequipa, Per\u00fa","institution_ids":["https://openalex.org/I120753068"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022613503","display_name":"Luciano Arnaldo Romero Calla","orcid":"https://orcid.org/0000-0002-6186-4027"},"institutions":[{"id":"https://openalex.org/I161127581","display_name":"Universidade Federal Fluminense","ror":"https://ror.org/02rjhbb08","country_code":"BR","type":"education","lineage":["https://openalex.org/I161127581"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Luciano Arnaldo Romero Calla","raw_affiliation_strings":["Instituto de Computa\u00e7\u00e3o, Universidade Federal Fluminense, Niteroi, Rio de Janeiro, BR"],"affiliations":[{"raw_affiliation_string":"Instituto de Computa\u00e7\u00e3o, Universidade Federal Fluminense, Niteroi, Rio de Janeiro, BR","institution_ids":["https://openalex.org/I161127581"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054168465","display_name":"Lizeth Joseline Fuentes Perez","orcid":"https://orcid.org/0000-0003-1096-2871"},"institutions":[{"id":"https://openalex.org/I161127581","display_name":"Universidade Federal Fluminense","ror":"https://ror.org/02rjhbb08","country_code":"BR","type":"education","lineage":["https://openalex.org/I161127581"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Lizeth Joseline Fuentes Perez","raw_affiliation_strings":["Instituto de Computa\u00e7\u00e3o, Universidade Federal Fluminense, Niteroi, Rio de Janeiro, BR"],"affiliations":[{"raw_affiliation_string":"Instituto de Computa\u00e7\u00e3o, Universidade Federal Fluminense, Niteroi, Rio de Janeiro, BR","institution_ids":["https://openalex.org/I161127581"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5012304998"],"corresponding_institution_ids":["https://openalex.org/I120753068"],"apc_list":null,"apc_paid":null,"fwci":0.3249,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.62051869,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"2","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9995999932289124,"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":0.9995999932289124,"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/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9962000250816345,"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/computer-science","display_name":"Computer science","score":0.6592731475830078},{"id":"https://openalex.org/keywords/salient","display_name":"Salient","score":0.5566427111625671},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5173446536064148},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.48623982071876526},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.47054415941238403},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4626416265964508},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4489792585372925},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4273325204849243},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.41581153869628906},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38634034991264343},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.34179532527923584},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.08993622660636902}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6592731475830078},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.5566427111625671},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5173446536064148},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.48623982071876526},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.47054415941238403},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4626416265964508},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4489792585372925},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4273325204849243},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.41581153869628906},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38634034991264343},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.34179532527923584},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.08993622660636902},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/clei.2015.7359459","is_oa":false,"landing_page_url":"https://doi.org/10.1109/clei.2015.7359459","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 Latin American Computing Conference (CLEI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6399999856948853,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W93676430","https://openalex.org/W2020682184","https://openalex.org/W2031878977","https://openalex.org/W2100657858","https://openalex.org/W2102838323","https://openalex.org/W2106629076","https://openalex.org/W2107216992","https://openalex.org/W2117183049","https://openalex.org/W2138707442","https://openalex.org/W2155957710","https://openalex.org/W2295382923","https://openalex.org/W6676085277","https://openalex.org/W6680778942"],"related_works":["https://openalex.org/W2329500892","https://openalex.org/W28991112","https://openalex.org/W2370726991","https://openalex.org/W2369710579","https://openalex.org/W4327728159","https://openalex.org/W4394266730","https://openalex.org/W1990856605","https://openalex.org/W2053783616","https://openalex.org/W4388913932","https://openalex.org/W4309130263"],"abstract_inverted_index":{"Due":[0],"to":[1,35,82,104],"the":[2,8,45,55,71,91,95,99,131,141,146],"increasing":[3],"amount":[4],"of":[5,10,44,70,119,143,145],"data":[6,14],"and":[7,26,38,117,127],"reduction":[9],"costs":[11],"in":[12,23,51,86,101,129],"3D":[13,32,52,87,112],"acquisition":[15],"devices,":[16],"there":[17],"has":[18],"been":[19],"a":[20,79],"growing":[21],"interest,":[22],"developing":[24],"efficient":[25],"robust":[27],"feature":[28,49],"extraction":[29,50],"algorithms":[30,106],"for":[31,48],"shapes,":[33],"invariants":[34],"isometric,":[36],"topological":[37],"noise":[39],"changes,":[40],"among":[41],"others.":[42],"One":[43],"key":[46],"tasks":[47],"shapes":[53,88],"is":[54,125,134],"interest":[56,60,84],"points":[57,61,85],"detection;":[58],"where":[59,138],"are":[62],"salient":[63],"structures,":[64],"which":[65,97],"can":[66],"be":[67],"used,":[68],"instead":[69],"whole":[72],"object.":[73],"In":[74],"this":[75],"research,":[76],"we":[77],"present":[78],"new":[80],"approach":[81],"detect":[83],"by":[89],"analyzing":[90],"triangles":[92],"that":[93,122],"compose":[94],"mesh":[96],"represent":[98],"shape,":[100],"different":[102],"way":[103],"other":[105],"more":[107],"complex":[108],"such":[109],"as":[110],"Harris":[111],"or":[113],"HKS.":[114],"Our":[115],"results":[116],"experiments":[118],"repeatability,":[120],"confirm":[121],"our":[123],"algorithm":[124],"stable":[126],"robust,":[128],"addition,":[130],"computational":[132],"complexity":[133],"O(n":[135],"log":[136],"n),":[137],"n":[139],"represents":[140],"number":[142],"faces":[144],"mesh.":[147]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
