{"id":"https://openalex.org/W4205776365","doi":"https://doi.org/10.1109/ic-nidc54101.2021.9660579","title":"Video Summarization Based on Fusing Features and Shot Segmentation","display_name":"Video Summarization Based on Fusing Features and Shot Segmentation","publication_year":2021,"publication_date":"2021-11-17","ids":{"openalex":"https://openalex.org/W4205776365","doi":"https://doi.org/10.1109/ic-nidc54101.2021.9660579"},"language":"en","primary_location":{"id":"doi:10.1109/ic-nidc54101.2021.9660579","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ic-nidc54101.2021.9660579","pdf_url":null,"source":{"id":"https://openalex.org/S4363608589","display_name":"2021 7th IEEE International Conference on Network Intelligence and Digital Content (IC-NIDC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 7th IEEE International Conference on Network Intelligence and Digital Content (IC-NIDC)","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/A5004016242","display_name":"Xuming Feng","orcid":null},"institutions":[{"id":"https://openalex.org/I75689368","display_name":"Communication University of China","ror":"https://ror.org/04facbs33","country_code":"CN","type":"education","lineage":["https://openalex.org/I75689368"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuming Feng","raw_affiliation_strings":["State Key Laboratory of Media Convergence and Communication, Communication University of China, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Media Convergence and Communication, Communication University of China, Beijing, China","institution_ids":["https://openalex.org/I75689368"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101564873","display_name":"Yaping Zhu","orcid":"https://orcid.org/0000-0002-8150-6366"},"institutions":[{"id":"https://openalex.org/I75689368","display_name":"Communication University of China","ror":"https://ror.org/04facbs33","country_code":"CN","type":"education","lineage":["https://openalex.org/I75689368"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaping Zhu","raw_affiliation_strings":["State Key Laboratory of Media Convergence and Communication, Communication University of China, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Media Convergence and Communication, Communication University of China, Beijing, China","institution_ids":["https://openalex.org/I75689368"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5115598536","display_name":"Cheng Yang","orcid":"https://orcid.org/0000-0002-9692-9564"},"institutions":[{"id":"https://openalex.org/I75689368","display_name":"Communication University of China","ror":"https://ror.org/04facbs33","country_code":"CN","type":"education","lineage":["https://openalex.org/I75689368"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cheng Yang","raw_affiliation_strings":["State Key Laboratory of Media Convergence and Communication, Communication University of China, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Media Convergence and Communication, Communication University of China, Beijing, China","institution_ids":["https://openalex.org/I75689368"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I75689368"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"383","last_page":"387"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11439","display_name":"Video Analysis and Summarization","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/T11439","display_name":"Video Analysis and Summarization","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/T11309","display_name":"Music and Audio Processing","score":0.9954000115394592,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9664999842643738,"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/automatic-summarization","display_name":"Automatic summarization","score":0.8916348218917847},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8883097171783447},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7810430526733398},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6723247766494751},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6313814520835876},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.579278826713562},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5746278762817383},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.5435253977775574},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5020549297332764},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.4904274642467499},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.48519328236579895},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4834228754043579},{"id":"https://openalex.org/keywords/video-processing","display_name":"Video processing","score":0.4652811884880066},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.45502761006355286},{"id":"https://openalex.org/keywords/shot","display_name":"Shot (pellet)","score":0.43113645911216736}],"concepts":[{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.8916348218917847},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8883097171783447},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7810430526733398},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6723247766494751},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6313814520835876},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.579278826713562},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5746278762817383},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.5435253977775574},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5020549297332764},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.4904274642467499},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.48519328236579895},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4834228754043579},{"id":"https://openalex.org/C65483669","wikidata":"https://www.wikidata.org/wiki/Q3536669","display_name":"Video processing","level":2,"score":0.4652811884880066},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.45502761006355286},{"id":"https://openalex.org/C2778344882","wikidata":"https://www.wikidata.org/wiki/Q278938","display_name":"Shot (pellet)","level":2,"score":0.43113645911216736},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ic-nidc54101.2021.9660579","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ic-nidc54101.2021.9660579","pdf_url":null,"source":{"id":"https://openalex.org/S4363608589","display_name":"2021 7th IEEE International Conference on Network Intelligence and Digital Content (IC-NIDC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 7th IEEE International Conference on Network Intelligence and Digital Content (IC-NIDC)","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":28,"referenced_works":["https://openalex.org/W1904325426","https://openalex.org/W1924343884","https://openalex.org/W1966872876","https://openalex.org/W2012592962","https://openalex.org/W2076866895","https://openalex.org/W2097117768","https://openalex.org/W2147661572","https://openalex.org/W2529272619","https://openalex.org/W2607326921","https://openalex.org/W2617122763","https://openalex.org/W2620629206","https://openalex.org/W2737677090","https://openalex.org/W2769795331","https://openalex.org/W2781922022","https://openalex.org/W2895758197","https://openalex.org/W2902616437","https://openalex.org/W2963703618","https://openalex.org/W2963877232","https://openalex.org/W2963919999","https://openalex.org/W3006565055","https://openalex.org/W3010790568","https://openalex.org/W3107128832","https://openalex.org/W3107783769","https://openalex.org/W3171941639","https://openalex.org/W6640109428","https://openalex.org/W6743446608","https://openalex.org/W6747656205","https://openalex.org/W6756070665"],"related_works":["https://openalex.org/W2366403280","https://openalex.org/W1495108544","https://openalex.org/W2091301346","https://openalex.org/W3148229873","https://openalex.org/W4389760904","https://openalex.org/W2150160875","https://openalex.org/W4242223894","https://openalex.org/W4306886878","https://openalex.org/W1517524280","https://openalex.org/W2182261604"],"abstract_inverted_index":{"Video":[0],"summarization":[1,20],"is":[2],"a":[3,55,79],"technique":[4],"that":[5],"creates":[6],"short":[7],"summaries":[8],"from":[9],"original":[10,110],"videos":[11,38],"while":[12],"retaining":[13],"the":[14,30,48,67,74,85,90,98,101,109,123],"main":[15],"representative":[16],"information.":[17],"Traditional":[18],"video":[19,99,111],"models":[21],"based":[22,58,83],"on":[23,59,84,115],"deep":[24,102],"learning":[25],"mostly":[26],"use":[27],"frames":[28],"as":[29],"basic":[31],"processing":[32],"unit,":[33],"which":[34,64,88],"cannot":[35],"handle":[36],"long":[37],"due":[39],"to":[40,107],"hardware":[41],"limitations.":[42],"In":[43],"this":[44],"paper,":[45],"we":[46,77],"compress":[47],"frame-level":[49],"features":[50,53,92,96,103],"into":[51,100],"shot-level":[52],"using":[54],"feature":[56,80],"extractor":[57],"Convolutional":[60],"Neural":[61],"Network":[62],"(CNN),":[63],"can":[65],"improve":[66],"training":[68],"accuracy":[69],"and":[70,93,120],"reduce":[71],"computation.":[72],"At":[73],"same":[75],"time,":[76],"propose":[78],"fusion":[81],"algorithm":[82],"capsule":[86],"network,":[87],"combines":[89],"RGB":[91],"Light":[94],"Flow":[95],"of":[97,125],"with":[104],"adaptive":[105],"weights":[106],"enhance":[108],"features.":[112],"Experiment":[113],"results":[114],"two":[116],"benchmark":[117],"datasets":[118],"(TVsum":[119],"SumMe)":[121],"validate":[122],"effectiveness":[124],"our":[126],"method.":[127]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}