{"id":"https://openalex.org/W2786105602","doi":"https://doi.org/10.1109/3dtv.2017.8280401","title":"Adaptive filter for denoising 3D data captured by depth sensors","display_name":"Adaptive filter for denoising 3D data captured by depth sensors","publication_year":2017,"publication_date":"2017-06-01","ids":{"openalex":"https://openalex.org/W2786105602","doi":"https://doi.org/10.1109/3dtv.2017.8280401","mag":"2786105602"},"language":"en","primary_location":{"id":"doi:10.1109/3dtv.2017.8280401","is_oa":false,"landing_page_url":"https://doi.org/10.1109/3dtv.2017.8280401","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 3DTV Conference: The True Vision - Capture, Transmission and Display of 3D Video (3DTV-CON)","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/A5028640677","display_name":"Somar Boubou","orcid":null},"institutions":[{"id":"https://openalex.org/I4840577","display_name":"Toyota Technological Institute","ror":"https://ror.org/001hv0k59","country_code":"JP","type":"education","lineage":["https://openalex.org/I4840577"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Somar Boubou","raw_affiliation_strings":["Department of Advanced Science and Technology, Toyota Technological Institute, Tempaku, Nagoya, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Advanced Science and Technology, Toyota Technological Institute, Tempaku, Nagoya, Japan","institution_ids":["https://openalex.org/I4840577"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036052448","display_name":"Tatsuo Narikiyo","orcid":"https://orcid.org/0000-0002-1610-7270"},"institutions":[{"id":"https://openalex.org/I4840577","display_name":"Toyota Technological Institute","ror":"https://ror.org/001hv0k59","country_code":"JP","type":"education","lineage":["https://openalex.org/I4840577"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tatsuo Narikiyo","raw_affiliation_strings":["Department of Advanced Science and Technology, Toyota Technological Institute, Tempaku, Nagoya, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Advanced Science and Technology, Toyota Technological Institute, Tempaku, Nagoya, Japan","institution_ids":["https://openalex.org/I4840577"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053280611","display_name":"Michihiro Kawanishi","orcid":"https://orcid.org/0000-0003-4013-1593"},"institutions":[{"id":"https://openalex.org/I4840577","display_name":"Toyota Technological Institute","ror":"https://ror.org/001hv0k59","country_code":"JP","type":"education","lineage":["https://openalex.org/I4840577"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Michihiro Kawanishi","raw_affiliation_strings":["Department of Advanced Science and Technology, Toyota Technological Institute, Tempaku, Nagoya, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Advanced Science and Technology, Toyota Technological Institute, Tempaku, Nagoya, Japan","institution_ids":["https://openalex.org/I4840577"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5028640677"],"corresponding_institution_ids":["https://openalex.org/I4840577"],"apc_list":null,"apc_paid":null,"fwci":0.5461,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.76862047,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"48","issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9993000030517578,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9993000030517578,"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/T10638","display_name":"Optical measurement and interference techniques","score":0.9968000054359436,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9965000152587891,"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/noise-reduction","display_name":"Noise reduction","score":0.766045093536377},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6925065517425537},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6800427436828613},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.6382598876953125},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5824944972991943},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.5145406126976013},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5072362422943115},{"id":"https://openalex.org/keywords/video-denoising","display_name":"Video denoising","score":0.49991607666015625},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.49878668785095215},{"id":"https://openalex.org/keywords/adaptive-filter","display_name":"Adaptive filter","score":0.42071372270584106},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.36929863691329956},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.20131027698516846},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.12572887539863586},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.09714961051940918}],"concepts":[{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.766045093536377},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6925065517425537},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6800427436828613},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.6382598876953125},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5824944972991943},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.5145406126976013},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5072362422943115},{"id":"https://openalex.org/C30814859","wikidata":"https://www.wikidata.org/wiki/Q4119603","display_name":"Video denoising","level":5,"score":0.49991607666015625},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.49878668785095215},{"id":"https://openalex.org/C102248274","wikidata":"https://www.wikidata.org/wiki/Q168388","display_name":"Adaptive filter","level":2,"score":0.42071372270584106},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.36929863691329956},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.20131027698516846},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.12572887539863586},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.09714961051940918},{"id":"https://openalex.org/C23431618","wikidata":"https://www.wikidata.org/wiki/Q1404672","display_name":"Multiview Video Coding","level":4,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/3dtv.2017.8280401","is_oa":false,"landing_page_url":"https://doi.org/10.1109/3dtv.2017.8280401","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 3DTV Conference: The True Vision - Capture, Transmission and Display of 3D Video (3DTV-CON)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W75517964","https://openalex.org/W1509167548","https://openalex.org/W1526134577","https://openalex.org/W1568085006","https://openalex.org/W1795772705","https://openalex.org/W2039039026","https://openalex.org/W2042014704","https://openalex.org/W2043980245","https://openalex.org/W2046464221","https://openalex.org/W2049776679","https://openalex.org/W2063668503","https://openalex.org/W2070961462","https://openalex.org/W2085735683","https://openalex.org/W2106816388","https://openalex.org/W2115977394","https://openalex.org/W2156222070","https://openalex.org/W2201791961","https://openalex.org/W2402704303","https://openalex.org/W2566131234","https://openalex.org/W2568788818","https://openalex.org/W6603017118","https://openalex.org/W6630621609","https://openalex.org/W6638509869","https://openalex.org/W6666471264","https://openalex.org/W6677229830"],"related_works":["https://openalex.org/W2387796150","https://openalex.org/W1987356308","https://openalex.org/W3119800349","https://openalex.org/W4385272703","https://openalex.org/W2513570774","https://openalex.org/W2139368882","https://openalex.org/W4214691059","https://openalex.org/W4287907666","https://openalex.org/W2792992868","https://openalex.org/W2997240037"],"abstract_inverted_index":{"Current":[0],"consumer":[1],"depth":[2,5,21,26,36,59,78,117],"sensors":[3,28],"produce":[4],"maps":[6],"that":[7,137],"are":[8,55],"often":[9],"noisy":[10],"and":[11],"lack":[12],"sufficient":[13],"detail.":[14],"Enhancing":[15],"the":[16,19,45,58,82,95,104,142],"quality":[17],"of":[18,57,84,97,122,125],"3D":[20,77],"data":[22,37,106],"obtained":[23],"from":[24,76,116],"compact":[25],"Kinect-like":[27],"is":[29,38],"an":[30],"increasingly":[31],"popular":[32],"research":[33],"area.":[34],"Although":[35],"known":[39],"to":[40,50,72,112],"carry":[41],"a":[42,67,132],"signal-dependent":[43],"noise,":[44],"state-of-the-art":[46,91,143],"denoising":[47,52,70,87,103],"methods":[48],"tend":[49],"employ":[51],"techniques":[53],"which":[54],"independent":[56],"signal":[60],"itself.":[61],"In":[62,110],"this":[63],"paper,":[64],"we":[65,119],"present":[66],"novel":[68],"adaptive":[69],"filter":[71,88,140],"enhance":[73],"object":[74,98,114],"recognition":[75,99,115],"data.":[79],"We":[80],"evaluate":[81],"performance":[83],"our":[85,138],"proposed":[86,139],"against":[89],"other":[90],"filters":[92],"based":[93],"on":[94],"enhancement":[96],"accuracy":[100],"achieved":[101],"after":[102],"raw":[105],"with":[107,131],"each":[108],"filter.":[109],"order":[111],"perform":[113],"data,":[118],"make":[120],"use":[121],"Differential":[123],"Histogram":[124],"Normal":[126],"Vectors":[127],"(DHONV)":[128],"features":[129],"along":[130],"linear":[133],"SVM.":[134],"Experiments":[135],"show":[136],"outperformed":[141],"de-noising":[144],"methods.":[145]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}