{"id":"https://openalex.org/W2324354308","doi":"https://doi.org/10.1109/mfi.2014.6997755","title":"Object segmentation and recognition in 3D point cloud with language model","display_name":"Object segmentation and recognition in 3D point cloud with language model","publication_year":2014,"publication_date":"2014-09-01","ids":{"openalex":"https://openalex.org/W2324354308","doi":"https://doi.org/10.1109/mfi.2014.6997755","mag":"2324354308"},"language":"en","primary_location":{"id":"doi:10.1109/mfi.2014.6997755","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mfi.2014.6997755","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 International Conference on Multisensor Fusion and Information Integration for Intelligent Systems (MFI)","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/A5062124960","display_name":"Yi Yang","orcid":"https://orcid.org/0000-0003-3964-2433"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yang Yi","raw_affiliation_strings":["School of Automation, Beijing Institute of Technology, Beijing"],"affiliations":[{"raw_affiliation_string":"School of Automation, Beijing Institute of Technology, Beijing","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040670761","display_name":"Yan Guang","orcid":null},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Guang","raw_affiliation_strings":["School of Automation, Beijing Institute of Technology, Beijing"],"affiliations":[{"raw_affiliation_string":"School of Automation, Beijing Institute of Technology, Beijing","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zhu Hao","orcid":null},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhu Hao","raw_affiliation_strings":["School of Automation, Beijing Institute of Technology, Beijing"],"affiliations":[{"raw_affiliation_string":"School of Automation, Beijing Institute of Technology, Beijing","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091459774","display_name":"Mengyin Fu","orcid":"https://orcid.org/0000-0002-5520-7127"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fu Meng-yin","raw_affiliation_strings":["School of Automation, Beijing Institute of Technology, Beijing"],"affiliations":[{"raw_affiliation_string":"School of Automation, Beijing Institute of Technology, Beijing","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":null,"display_name":"Wang Mei-ling","orcid":null},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wang Mei-ling","raw_affiliation_strings":["School of Automation, Beijing Institute of Technology, Beijing"],"affiliations":[{"raw_affiliation_string":"School of Automation, Beijing Institute of Technology, Beijing","institution_ids":["https://openalex.org/I125839683"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5062124960"],"corresponding_institution_ids":["https://openalex.org/I125839683"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.58758886,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"44","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9993000030517578,"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"}},"topics":[{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9993000030517578,"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"}},{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9991000294685364,"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/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8098208904266357},{"id":"https://openalex.org/keywords/scale-invariant-feature-transform","display_name":"Scale-invariant feature transform","score":0.7669074535369873},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.744583010673523},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.6434631943702698},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.6092396974563599},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.580201268196106},{"id":"https://openalex.org/keywords/bag-of-words-model","display_name":"Bag-of-words model","score":0.5291129946708679},{"id":"https://openalex.org/keywords/bag-of-words-model-in-computer-vision","display_name":"Bag-of-words model in computer vision","score":0.49942684173583984},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.49454471468925476},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4807407855987549},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.48026180267333984},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.45873135328292847},{"id":"https://openalex.org/keywords/3d-single-object-recognition","display_name":"3D single-object recognition","score":0.445229172706604},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.42142999172210693},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.4147006869316101},{"id":"https://openalex.org/keywords/visual-word","display_name":"Visual Word","score":0.3306248188018799},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.2623322010040283},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.154608815908432}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8098208904266357},{"id":"https://openalex.org/C61265191","wikidata":"https://www.wikidata.org/wiki/Q767770","display_name":"Scale-invariant feature transform","level":3,"score":0.7669074535369873},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.744583010673523},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.6434631943702698},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.6092396974563599},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.580201268196106},{"id":"https://openalex.org/C13672336","wikidata":"https://www.wikidata.org/wiki/Q3460803","display_name":"Bag-of-words model","level":2,"score":0.5291129946708679},{"id":"https://openalex.org/C167611913","wikidata":"https://www.wikidata.org/wiki/Q6884747","display_name":"Bag-of-words model in computer vision","level":5,"score":0.49942684173583984},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.49454471468925476},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4807407855987549},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.48026180267333984},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.45873135328292847},{"id":"https://openalex.org/C14551309","wikidata":"https://www.wikidata.org/wiki/Q4636325","display_name":"3D single-object recognition","level":4,"score":0.445229172706604},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.42142999172210693},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.4147006869316101},{"id":"https://openalex.org/C189391414","wikidata":"https://www.wikidata.org/wiki/Q7936579","display_name":"Visual Word","level":4,"score":0.3306248188018799},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.2623322010040283},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.154608815908432}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mfi.2014.6997755","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mfi.2014.6997755","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 International Conference on Multisensor Fusion and Information Integration for Intelligent Systems (MFI)","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":23,"referenced_works":["https://openalex.org/W21187803","https://openalex.org/W1482825550","https://openalex.org/W1499909935","https://openalex.org/W1570864891","https://openalex.org/W1837140482","https://openalex.org/W1967688818","https://openalex.org/W1968343087","https://openalex.org/W2053939793","https://openalex.org/W2062874246","https://openalex.org/W2115703234","https://openalex.org/W2124386111","https://openalex.org/W2124767316","https://openalex.org/W2125517557","https://openalex.org/W2128017662","https://openalex.org/W2132606888","https://openalex.org/W2150066425","https://openalex.org/W2151322733","https://openalex.org/W2160821342","https://openalex.org/W2750339080","https://openalex.org/W4206765718","https://openalex.org/W6677132883","https://openalex.org/W6679759492","https://openalex.org/W6682239955"],"related_works":["https://openalex.org/W1615295117","https://openalex.org/W2158102958","https://openalex.org/W2035094092","https://openalex.org/W2277784908","https://openalex.org/W2045213079","https://openalex.org/W2938717424","https://openalex.org/W2350926174","https://openalex.org/W2473933584","https://openalex.org/W2412408867","https://openalex.org/W2587721114"],"abstract_inverted_index":{"We":[0],"proposed":[1,54,78],"a":[2,37,45,55,79],"recognition":[3,15,80],"algorithm":[4,81],"based":[5,59,82],"on":[6,60,83,113],"feature":[7,56],"extraction":[8,57],"and":[9,41,44,63,70,85],"Bag-of-words":[10],"with":[11,68],"language":[12,86],"model.":[13],"Object":[14],"in":[16,30,72],"3D":[17,61,73],"rang":[18],"data":[19,116],"of":[20,101],"big":[21],"scene":[22],"has":[23],"become":[24],"an":[25],"increasingly":[26],"popular":[27],"research":[28],"topic":[29],"intelligent":[31],"vehicle":[32],"area.":[33],"Firstly":[34],"we":[35,53,77],"introduce":[36],"fast":[38],"ground":[39],"filtering":[40],"clustering":[42],"method":[43,47,58],"convenient":[46],"to":[48,65,93,96],"generation":[49],"training":[50],"samples.":[51],"Then":[52],"SIFT":[62],"FPFH":[64],"get":[66],"descriptors":[67],"scale-invariant":[69],"rotation-invariant":[71],"range":[74],"data.":[75],"Furthermore,":[76],"bag-of-words":[84,94],"model":[87,95],"by":[88],"add":[89],"spatial":[90],"semantic":[91],"information":[92],"make":[97],"up":[98],"the":[99,103,106],"shortcoming":[100],"ignoring":[102],"relationships":[104],"between":[105],"visual":[107],"words.":[108],"At":[109],"last,":[110],"experimental":[111],"results":[112],"real":[114],"laser":[115],"depicting":[117],"rural":[118],"scenes":[119],"are":[120],"presented.":[121]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2026-04-16T08:26:57.006410","created_date":"2025-10-10T00:00:00"}