{"id":"https://openalex.org/W2905443570","doi":"https://doi.org/10.1145/3282894.3289728","title":"Preliminary Investigation of Object-based Activity Recognition Using Egocentric Video Based on Web Knowledge","display_name":"Preliminary Investigation of Object-based Activity Recognition Using Egocentric Video Based on Web Knowledge","publication_year":2018,"publication_date":"2018-11-25","ids":{"openalex":"https://openalex.org/W2905443570","doi":"https://doi.org/10.1145/3282894.3289728","mag":"2905443570"},"language":"en","primary_location":{"id":"doi:10.1145/3282894.3289728","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3282894.3289728","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 17th International Conference on Mobile and Ubiquitous Multimedia","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/A5036198825","display_name":"Tomoya Nakatani","orcid":null},"institutions":[{"id":"https://openalex.org/I98285908","display_name":"The University of Osaka","ror":"https://ror.org/035t8zc32","country_code":"JP","type":"education","lineage":["https://openalex.org/I98285908"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tomoya Nakatani","raw_affiliation_strings":["Osaka University, Yamadaoka, Suita, Osaka, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Osaka University, Yamadaoka, Suita, Osaka, Japan","institution_ids":["https://openalex.org/I98285908"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023117346","display_name":"Ryohei Kuga","orcid":null},"institutions":[{"id":"https://openalex.org/I98285908","display_name":"The University of Osaka","ror":"https://ror.org/035t8zc32","country_code":"JP","type":"education","lineage":["https://openalex.org/I98285908"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ryohei Kuga","raw_affiliation_strings":["Osaka University, Yamadaoka, Suita, Osaka, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Osaka University, Yamadaoka, Suita, Osaka, Japan","institution_ids":["https://openalex.org/I98285908"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039456378","display_name":"Takuya Maekawa","orcid":"https://orcid.org/0000-0002-7227-580X"},"institutions":[{"id":"https://openalex.org/I98285908","display_name":"The University of Osaka","ror":"https://ror.org/035t8zc32","country_code":"JP","type":"education","lineage":["https://openalex.org/I98285908"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takuya Maekawa","raw_affiliation_strings":["Osaka University, Yamadaoka, Suita, Osaka, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Osaka University, Yamadaoka, Suita, Osaka, Japan","institution_ids":["https://openalex.org/I98285908"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I98285908"],"apc_list":null,"apc_paid":null,"fwci":0.2081,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.57277635,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"375","last_page":"381"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9998000264167786,"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9998000264167786,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9991000294685364,"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":0.9980000257492065,"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":0.8043136596679688},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6999782919883728},{"id":"https://openalex.org/keywords/activity-recognition","display_name":"Activity recognition","score":0.6812560558319092},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.643349826335907},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.613004207611084},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5490322113037109},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5480518341064453},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.524653434753418},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.43605560064315796},{"id":"https://openalex.org/keywords/wearable-computer","display_name":"Wearable computer","score":0.4195733964443207},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.36858323216438293},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.33601269125938416},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.24734365940093994}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8043136596679688},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6999782919883728},{"id":"https://openalex.org/C121687571","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity recognition","level":2,"score":0.6812560558319092},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.643349826335907},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.613004207611084},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5490322113037109},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5480518341064453},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.524653434753418},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.43605560064315796},{"id":"https://openalex.org/C150594956","wikidata":"https://www.wikidata.org/wiki/Q1334829","display_name":"Wearable computer","level":2,"score":0.4195733964443207},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.36858323216438293},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33601269125938416},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.24734365940093994},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3282894.3289728","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3282894.3289728","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 17th International Conference on Mobile and Ubiquitous Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"},{"id":"https://openalex.org/F4320338075","display_name":"Core Research for Evolutional Science and Technology","ror":"https://ror.org/00097mb19"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W166064277","https://openalex.org/W179321503","https://openalex.org/W1497385253","https://openalex.org/W1510835000","https://openalex.org/W1517086206","https://openalex.org/W1897824230","https://openalex.org/W1969307352","https://openalex.org/W1980909913","https://openalex.org/W1993138654","https://openalex.org/W2003637680","https://openalex.org/W2009694489","https://openalex.org/W2097295641","https://openalex.org/W2105046342","https://openalex.org/W2125055259","https://openalex.org/W2128884492","https://openalex.org/W2135450947","https://openalex.org/W2148010363","https://openalex.org/W2155893237","https://openalex.org/W2163605009","https://openalex.org/W2165605600","https://openalex.org/W2168356304","https://openalex.org/W2387799167","https://openalex.org/W2482419090","https://openalex.org/W4301045096"],"related_works":["https://openalex.org/W3195649134","https://openalex.org/W4293226380","https://openalex.org/W2281498195","https://openalex.org/W2017526120","https://openalex.org/W2610664080","https://openalex.org/W2188304107","https://openalex.org/W2117913171","https://openalex.org/W3105278570","https://openalex.org/W2582769230","https://openalex.org/W3185156046"],"abstract_inverted_index":{"This":[0],"study":[1],"shows":[2],"a":[3,12,21,47,69,117,134,142],"preliminary":[4],"investigation":[5],"of":[6,80,119,136,144,165],"daily":[7],"activity":[8,63,79,93,102,146,154,164],"recognition":[9],"based":[10,148],"on":[11,46,110,149],"wearable":[13],"camera":[14],"without":[15,103],"using":[16,68,83,104],"training":[17,105],"data":[18,50],"prepared":[19],"by":[20],"user":[22,82],"in":[23,60,91],"her":[24,65],"environment.":[25],"Recently,":[26],"deep":[27,40],"learning":[28],"frameworks":[29],"have":[30],"been":[31],"publicly":[32],"available,":[33],"and":[34,125,141],"we":[35,55,107,129],"can":[36],"now":[37],"easily":[38],"use":[39],"convolutional":[41],"neural":[42],"networks":[43],"(CNNs)":[44],"pre-trained":[45,70],"large":[48],"image":[49],"set.":[51],"In":[52],"our":[53],"method,":[54],"first":[56],"detect":[57],"objects":[58,89],"used":[59,90],"the":[61,81,84,97,101,111,114,137,150,157,162,166],"user's":[62],"from":[64],"first-person":[66],"images":[67],"CNN":[71],"for":[72],"object":[73,85,139],"recognition.":[74],"We":[75],"then":[76],"estimate":[77,100],"an":[78,92],"detection":[86],"result":[87],"because":[88,113],"strongly":[94],"relate":[95],"to":[96],"activity.":[98],"To":[99],"data,":[106],"utilize":[108],"knowledge":[109,120],"Web":[112,115,151],"is":[116,161],"repository":[118],"that":[121],"reflects":[122],"real-world":[123],"events":[124],"common":[126],"sense.":[127],"Specifically,":[128],"compute":[130],"semantic":[131],"similarity":[132,159],"between":[133],"list":[135],"detected":[138],"names":[140],"name":[143],"each":[145],"class":[147,155],"knowledge.":[152],"The":[153],"with":[156],"largest":[158],"value":[160],"estimated":[163],"user.":[167]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
