{"id":"https://openalex.org/W4402219163","doi":"https://doi.org/10.1109/icrca60878.2024.10649311","title":"A Space Information-Enhanced Dense Video Caption for Indoor Human Action Recognition","display_name":"A Space Information-Enhanced Dense Video Caption for Indoor Human Action Recognition","publication_year":2024,"publication_date":"2024-01-12","ids":{"openalex":"https://openalex.org/W4402219163","doi":"https://doi.org/10.1109/icrca60878.2024.10649311"},"language":"en","primary_location":{"id":"doi:10.1109/icrca60878.2024.10649311","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icrca60878.2024.10649311","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 8th International Conference on Robotics, Control and Automation (ICRCA)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100427364","display_name":"Bin Chen","orcid":"https://orcid.org/0000-0002-6708-4101"},"institutions":[{"id":"https://openalex.org/I135598925","display_name":"Kyushu University","ror":"https://ror.org/00p4k0j84","country_code":"JP","type":"education","lineage":["https://openalex.org/I135598925"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Bin CHEN","raw_affiliation_strings":["ISEE. Kyushu University, Kyushu University,Fukuoka,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ISEE. Kyushu University, Kyushu University,Fukuoka,Japan","institution_ids":["https://openalex.org/I135598925"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017062920","display_name":"Yugo Nakamura","orcid":"https://orcid.org/0000-0002-8834-5323"},"institutions":[{"id":"https://openalex.org/I135598925","display_name":"Kyushu University","ror":"https://ror.org/00p4k0j84","country_code":"JP","type":"education","lineage":["https://openalex.org/I135598925"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yugo NAKAMURA","raw_affiliation_strings":["ISEE. Kyushu University, Kyushu University,Fukuoka,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ISEE. Kyushu University, Kyushu University,Fukuoka,Japan","institution_ids":["https://openalex.org/I135598925"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101428987","display_name":"Shogo Fukushima","orcid":"https://orcid.org/0000-0003-1362-8078"},"institutions":[{"id":"https://openalex.org/I135598925","display_name":"Kyushu University","ror":"https://ror.org/00p4k0j84","country_code":"JP","type":"education","lineage":["https://openalex.org/I135598925"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shogo FUKUSHIMA","raw_affiliation_strings":["ISEE. Kyushu University, Kyushu University,Fukuoka,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ISEE. Kyushu University, Kyushu University,Fukuoka,Japan","institution_ids":["https://openalex.org/I135598925"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084986446","display_name":"Yutaka Arakawa","orcid":"https://orcid.org/0000-0002-7156-9160"},"institutions":[{"id":"https://openalex.org/I135598925","display_name":"Kyushu University","ror":"https://ror.org/00p4k0j84","country_code":"JP","type":"education","lineage":["https://openalex.org/I135598925"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yutaka ARAKAWA","raw_affiliation_strings":["ISEE. Kyushu University, Kyushu University,Fukuoka,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ISEE. Kyushu University, Kyushu University,Fukuoka,Japan","institution_ids":["https://openalex.org/I135598925"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I135598925"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"423","last_page":"427"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9998999834060669,"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":0.9998999834060669,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9997000098228455,"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":0.9883000254631042,"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/action-recognition","display_name":"Action recognition","score":0.6685559749603271},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6605325937271118},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.5714721083641052},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.561245322227478},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4018230438232422},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3466186225414276},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics (images)","score":0.33609139919281006},{"id":"https://openalex.org/keywords/multimedia","display_name":"Multimedia","score":0.3338509798049927},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.08757328987121582}],"concepts":[{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.6685559749603271},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6605325937271118},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.5714721083641052},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.561245322227478},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4018230438232422},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3466186225414276},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.33609139919281006},{"id":"https://openalex.org/C49774154","wikidata":"https://www.wikidata.org/wiki/Q131765","display_name":"Multimedia","level":1,"score":0.3338509798049927},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.08757328987121582},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icrca60878.2024.10649311","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icrca60878.2024.10649311","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 8th International Conference on Robotics, Control and Automation (ICRCA)","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":18,"referenced_works":["https://openalex.org/W1522734439","https://openalex.org/W1956340063","https://openalex.org/W2034443282","https://openalex.org/W2600463316","https://openalex.org/W2909888383","https://openalex.org/W2952132648","https://openalex.org/W2962799512","https://openalex.org/W3034815696","https://openalex.org/W3047922786","https://openalex.org/W3208474254","https://openalex.org/W4312815172","https://openalex.org/W4312936847","https://openalex.org/W4324080648","https://openalex.org/W4324313120","https://openalex.org/W4386066385","https://openalex.org/W4390872479","https://openalex.org/W6678262379","https://openalex.org/W6850813487"],"related_works":["https://openalex.org/W304855073","https://openalex.org/W2084487854","https://openalex.org/W2353878298","https://openalex.org/W372519479","https://openalex.org/W4205118967","https://openalex.org/W938111471","https://openalex.org/W2077682749","https://openalex.org/W2298450300","https://openalex.org/W1576128429","https://openalex.org/W2269464716"],"abstract_inverted_index":{"Dense":[0,132],"video":[1,63,96],"captioning":[2,97],"tasks":[3],"are":[4,74],"used":[5,27],"to":[6,25,55,58,92],"detect":[7],"interesting":[8,109],"events":[9,16],"and":[10,31,51,115,155,163],"provide":[11],"descriptive":[12],"text":[13],"for":[14,65,166],"these":[15,70],"from":[17],"untrimmed":[18],"videos.":[19],"This":[20],"technology":[21],"has":[22],"the":[23,40,45,78,81,108,116,127,131,146],"potential":[24],"be":[26],"in":[28,44,80],"security":[29],"surveillance":[30],"human":[32,67,72],"care":[33],"applications.":[34],"However,":[35],"current":[36],"methods":[37,98],"often":[38],"overlook":[39],"relationships":[41],"between":[42],"objects":[43,79,110],"video,":[46],"which":[47],"limits":[48],"their":[49],"applicability":[50],"makes":[52],"it":[53],"challenging":[54],"adapt":[56],"them":[57],"specific":[59],"domains,":[60],"such":[61],"as":[62],"summarization":[64],"indoor":[66],"activities.":[68],"In":[69,83],"scenarios,":[71],"activities":[73],"closely":[75],"intertwined":[76],"with":[77,99],"scene.":[82],"this":[84,124],"paper,":[85],"we":[86,103],"propose":[87],"a":[88,138,152,161],"plug-and-play":[89],"module":[90],"designed":[91],"enhance":[93],"existing":[94],"dense":[95],"spatial":[100,105],"information.":[101],"Specifically,":[102],"extract":[104],"information":[106,125],"about":[107],"using":[111,137],"Red-Green-Blue-Depth":[112],"(RGB-D)":[113],"images":[114],"results":[117],"of":[118,148],"image":[119],"segmentation.":[120],"We":[121,144],"then":[122],"integrate":[123],"into":[126],"captions":[128],"generated":[129],"by":[130],"Video":[133],"Captioning":[134],"(DVC)":[135],"method":[136],"fine-tuned":[139],"Large":[140],"Language":[141],"Model":[142],"(LLM).":[143],"evaluate":[145],"performance":[147],"our":[149,158],"model":[150],"on":[151],"custom":[153],"dataset":[154],"demonstrate":[156],"that":[157],"system":[159],"provides":[160],"convenient":[162],"effective":[164],"approach":[165],"obtaining":[167],"space-enhanced":[168],"captions.":[169]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}