{"id":"https://openalex.org/W4413018595","doi":"https://doi.org/10.1109/fg61629.2025.11099071","title":"MultiSensor-Home: A Wide-area Multi-modal Multi-view Dataset for Action Recognition and Transformer-based Sensor Fusion","display_name":"MultiSensor-Home: A Wide-area Multi-modal Multi-view Dataset for Action Recognition and Transformer-based Sensor Fusion","publication_year":2025,"publication_date":"2025-05-26","ids":{"openalex":"https://openalex.org/W4413018595","doi":"https://doi.org/10.1109/fg61629.2025.11099071"},"language":"en","primary_location":{"id":"doi:10.1109/fg61629.2025.11099071","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fg61629.2025.11099071","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 19th International Conference on Automatic Face and Gesture Recognition (FG)","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/A5101718798","display_name":"Trung Th\u00e0nh Nguy\u1ec5n","orcid":"https://orcid.org/0000-0001-8976-2922"},"institutions":[{"id":"https://openalex.org/I60134161","display_name":"Nagoya University","ror":"https://ror.org/04chrp450","country_code":"JP","type":"education","lineage":["https://openalex.org/I60134161"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Trung Thanh Nguyen","raw_affiliation_strings":["Nagoya University,Graduate School of Informatics,Nagoya,Aichi,Japan,464-8601"],"affiliations":[{"raw_affiliation_string":"Nagoya University,Graduate School of Informatics,Nagoya,Aichi,Japan,464-8601","institution_ids":["https://openalex.org/I60134161"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027960360","display_name":"Yasutomo Kawanishi","orcid":"https://orcid.org/0000-0002-3799-4550"},"institutions":[{"id":"https://openalex.org/I46980622","display_name":"Kyoto Seika University","ror":"https://ror.org/05g4f0342","country_code":"JP","type":"education","lineage":["https://openalex.org/I46980622"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yasutomo Kawanishi","raw_affiliation_strings":["Guardian Robot Project, Information R&#x0026;D and Strategy Headquarters, RIKEN,Seika,Kyoto,Japan,619-0288"],"affiliations":[{"raw_affiliation_string":"Guardian Robot Project, Information R&#x0026;D and Strategy Headquarters, RIKEN,Seika,Kyoto,Japan,619-0288","institution_ids":["https://openalex.org/I46980622"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007962043","display_name":"Vijay John","orcid":"https://orcid.org/0000-0002-9553-0906"},"institutions":[{"id":"https://openalex.org/I46980622","display_name":"Kyoto Seika University","ror":"https://ror.org/05g4f0342","country_code":"JP","type":"education","lineage":["https://openalex.org/I46980622"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Vijay John","raw_affiliation_strings":["Guardian Robot Project, Information R&#x0026;D and Strategy Headquarters, RIKEN,Seika,Kyoto,Japan,619-0288"],"affiliations":[{"raw_affiliation_string":"Guardian Robot Project, Information R&#x0026;D and Strategy Headquarters, RIKEN,Seika,Kyoto,Japan,619-0288","institution_ids":["https://openalex.org/I46980622"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047823141","display_name":"Takahiro Komamizu","orcid":"https://orcid.org/0000-0002-3041-4330"},"institutions":[{"id":"https://openalex.org/I60134161","display_name":"Nagoya University","ror":"https://ror.org/04chrp450","country_code":"JP","type":"education","lineage":["https://openalex.org/I60134161"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takahiro Komamizu","raw_affiliation_strings":["Nagoya University,Center for Artificial Intelligence, Mathematical and Data Science,Nagoya,Aichi,Japan,464-8601"],"affiliations":[{"raw_affiliation_string":"Nagoya University,Center for Artificial Intelligence, Mathematical and Data Science,Nagoya,Aichi,Japan,464-8601","institution_ids":["https://openalex.org/I60134161"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034941095","display_name":"Ichiro Ide","orcid":"https://orcid.org/0000-0003-3942-9296"},"institutions":[{"id":"https://openalex.org/I60134161","display_name":"Nagoya University","ror":"https://ror.org/04chrp450","country_code":"JP","type":"education","lineage":["https://openalex.org/I60134161"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ichiro Ide","raw_affiliation_strings":["Nagoya University,Graduate School of Informatics,Nagoya,Aichi,Japan,464-8601"],"affiliations":[{"raw_affiliation_string":"Nagoya University,Graduate School of Informatics,Nagoya,Aichi,Japan,464-8601","institution_ids":["https://openalex.org/I60134161"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101718798"],"corresponding_institution_ids":["https://openalex.org/I60134161"],"apc_list":null,"apc_paid":null,"fwci":2.66,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.90936227,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9761999845504761,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9761999845504761,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9142000079154968,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/modal","display_name":"Modal","score":0.7031283974647522},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.6371654868125916},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6335718631744385},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5454330444335938},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.5431894063949585},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5148453116416931},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.45293667912483215},{"id":"https://openalex.org/keywords/action-recognition","display_name":"Action recognition","score":0.45253145694732666},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3274754583835602},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.16526252031326294},{"id":"https://openalex.org/keywords/voltage","display_name":"Voltage","score":0.14924585819244385},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.06222429871559143}],"concepts":[{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.7031283974647522},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.6371654868125916},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6335718631744385},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5454330444335938},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.5431894063949585},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5148453116416931},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.45293667912483215},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.45253145694732666},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3274754583835602},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.16526252031326294},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.14924585819244385},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.06222429871559143},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fg61629.2025.11099071","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fg61629.2025.11099071","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 19th International Conference on Automatic Face and Gesture Recognition (FG)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322916","display_name":"Nagoya University","ror":"https://ror.org/04chrp450"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W54887220","https://openalex.org/W2054041160","https://openalex.org/W2810685774","https://openalex.org/W2944006115","https://openalex.org/W2963282966","https://openalex.org/W2964134613","https://openalex.org/W2981923053","https://openalex.org/W3011934803","https://openalex.org/W3034658206","https://openalex.org/W3088102655","https://openalex.org/W3091422730","https://openalex.org/W3104432418","https://openalex.org/W3106615203","https://openalex.org/W3126721948","https://openalex.org/W3138697035","https://openalex.org/W3158576998","https://openalex.org/W3196974791","https://openalex.org/W3199934435","https://openalex.org/W4214612132","https://openalex.org/W4221155627","https://openalex.org/W4231611928","https://openalex.org/W4282981352","https://openalex.org/W4304014690","https://openalex.org/W4319300928","https://openalex.org/W4385245566","https://openalex.org/W4386076580","https://openalex.org/W4403421698","https://openalex.org/W4403899609","https://openalex.org/W6631190155","https://openalex.org/W6726497184","https://openalex.org/W6783132704","https://openalex.org/W6791353385","https://openalex.org/W6797613833","https://openalex.org/W6864349371","https://openalex.org/W6868582632"],"related_works":["https://openalex.org/W2379392295","https://openalex.org/W3160965418","https://openalex.org/W613940353","https://openalex.org/W2320915480","https://openalex.org/W2099421762","https://openalex.org/W2132659060","https://openalex.org/W2031992971","https://openalex.org/W3214791684","https://openalex.org/W2152662039","https://openalex.org/W4283332100"],"abstract_inverted_index":{"Multi-modal":[0,80],"multi-view":[1,107,188],"action":[2,71,109,150,189],"recognition":[3,72,152],"is":[4],"a":[5,65,116,130],"rapidly":[6],"growing":[7],"field":[8],"in":[9,17,47,73,184],"computer":[10],"vision,":[11],"offering":[12],"significant":[13],"potential":[14],"for":[15,69],"applications":[16],"surveillance.":[18],"However,":[19],"current":[20],"datasets":[21,163],"often":[22],"fail":[23],"to":[24,120,134,142,148],"address":[25],"real-world":[26,186],"challenges":[27],"such":[28],"as":[29],"widearea":[30],"distributed":[31,96],"settings,":[32],"asynchronous":[33],"data":[34,103],"streams,":[35],"and":[36,52,76,101,159,174],"the":[37,62,79,126,140,151,156,160,165,170,178,181],"lack":[38],"of":[39,167,180],"frame-level":[40,108],"annotations.":[41],"Furthermore,":[42,125],"existing":[43,161],"methods":[44],"face":[45],"difficulties":[46],"effectively":[48],"modeling":[49],"inter-view":[50,123],"relationships":[51],"enhancing":[53],"spatial":[54,136],"feature":[55,137],"learning.":[56],"In":[57],"this":[58],"paper,":[59],"we":[60],"introduce":[61],"MultiSensor-Home":[63,89,158],"dataset,":[64],"novel":[66],"benchmark":[67],"designed":[68],"comprehensive":[70],"home":[74],"environments,":[75],"also":[77],"propose":[78],"Multi-view":[81],"Transformer-based":[82,117],"Sensor":[83],"Fusion":[84],"(MultiTSF)":[85],"method.":[86],"The":[87,111],"proposed":[88,112,127,157,182],"dataset":[90],"features":[91],"untrimmed":[92],"videos":[93],"captured":[94],"by":[95],"sensors,":[97],"providing":[98],"high-resolution":[99],"RGB":[100],"audio":[102],"along":[104],"with":[105,145],"detailed":[106],"labels.":[110],"MultiTSF":[113,168],"method":[114,128,183],"leverages":[115],"fusion":[118],"mechanism":[119],"dynamically":[121],"model":[122,141],"relationships.":[124],"integrates":[129],"human":[131,146],"detection":[132],"module":[133],"enhance":[135,149],"learning,":[138],"guiding":[139],"prioritize":[143],"frames":[144],"activity":[147],"accuracy.":[153],"Experiments":[154],"on":[155],"MM-Office":[162],"demonstrate":[164],"superiority":[166],"over":[169],"state-of-the-art":[171],"methods.":[172],"Quantitative":[173],"qualitative":[175],"results":[176],"highlight":[177],"effectiveness":[179],"advancing":[185],"multi-modal":[187],"recognition.":[190]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
