{"id":"https://openalex.org/W2030629622","doi":"https://doi.org/10.1145/1291233.1291275","title":"Efficient spatiotemporal-attention-driven shot matching","display_name":"Efficient spatiotemporal-attention-driven shot matching","publication_year":2007,"publication_date":"2007-09-29","ids":{"openalex":"https://openalex.org/W2030629622","doi":"https://doi.org/10.1145/1291233.1291275","mag":"2030629622"},"language":"en","primary_location":{"id":"doi:10.1145/1291233.1291275","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1291233.1291275","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 15th ACM international conference on 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/A5100324691","display_name":"Shan Li","orcid":"https://orcid.org/0000-0001-7923-3306"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Shan Li","raw_affiliation_strings":["The Chinese University of Hong Kong, Shatin, N.T., HI, Hong Kong","The Chinese University of Hong Kong, Shatin, N.T., HI, Hong Kong#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong, Shatin, N.T., HI, Hong Kong","institution_ids":["https://openalex.org/I177725633"]},{"raw_affiliation_string":"The Chinese University of Hong Kong, Shatin, N.T., HI, Hong Kong#TAB#","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057955111","display_name":"Moon-Chuen Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Moon-Chuen Lee","raw_affiliation_strings":["The Chinese University of Hong Kong, Shatin, N.T., Hong Kong","The Chinese University of Hong Kong, Shatin, N. T. Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong, Shatin, N.T., Hong Kong","institution_ids":["https://openalex.org/I177725633"]},{"raw_affiliation_string":"The Chinese University of Hong Kong, Shatin, N. T. Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.3162,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.81661721,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"178","last_page":"187"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","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/T11605","display_name":"Visual Attention and Saliency Detection","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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","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/T11439","display_name":"Video Analysis and Summarization","score":0.9995999932289124,"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":0.7720168828964233},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7335392236709595},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.730363667011261},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5505778789520264},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.5450232028961182},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5148991346359253},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4858967661857605},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.48541221022605896},{"id":"https://openalex.org/keywords/feature-matching","display_name":"Feature matching","score":0.42979440093040466},{"id":"https://openalex.org/keywords/grayscale","display_name":"Grayscale","score":0.42745715379714966},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.42410358786582947},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3228311240673065},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.29293394088745117},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12405312061309814}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7720168828964233},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7335392236709595},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.730363667011261},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5505778789520264},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.5450232028961182},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5148991346359253},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4858967661857605},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48541221022605896},{"id":"https://openalex.org/C2983787585","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Feature matching","level":3,"score":0.42979440093040466},{"id":"https://openalex.org/C78201319","wikidata":"https://www.wikidata.org/wiki/Q685727","display_name":"Grayscale","level":3,"score":0.42745715379714966},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.42410358786582947},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3228311240673065},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.29293394088745117},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12405312061309814},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/1291233.1291275","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1291233.1291275","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 15th ACM international conference on Multimedia","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":20,"referenced_works":["https://openalex.org/W176036590","https://openalex.org/W1497599070","https://openalex.org/W1558401404","https://openalex.org/W1964780534","https://openalex.org/W1965301399","https://openalex.org/W2053576891","https://openalex.org/W2062383499","https://openalex.org/W2099467003","https://openalex.org/W2107388002","https://openalex.org/W2114456882","https://openalex.org/W2118877769","https://openalex.org/W2119910902","https://openalex.org/W2126532873","https://openalex.org/W2129294557","https://openalex.org/W2136625207","https://openalex.org/W2145227859","https://openalex.org/W2153249803","https://openalex.org/W2158534059","https://openalex.org/W2169041475","https://openalex.org/W2170610624"],"related_works":["https://openalex.org/W2350424104","https://openalex.org/W2152949619","https://openalex.org/W1090580760","https://openalex.org/W2360393496","https://openalex.org/W4365793569","https://openalex.org/W2389991515","https://openalex.org/W2050706403","https://openalex.org/W2395120299","https://openalex.org/W2499438468","https://openalex.org/W2479744187"],"abstract_inverted_index":{"As":[0],"human":[1],"attention":[2,36,41,104,135],"is":[3,47,81,100,124,137],"an":[4,27,33,72,77],"effective":[5],"mechanism":[6],"for":[7,17,83],"information":[8],"prioritizing":[9],"and":[10,49,85],"selecting,":[11],"it":[12],"provides":[13],"a":[14],"practical":[15],"approach":[16],"intelligent":[18],"shot":[19,117],"similarity":[20,150],"matching.":[21,118,151],"In":[22],"this":[23],"paper,":[24],"we":[25],"propose":[26],"attention-driven":[28,128],"video":[29],"interpretation":[30],"method":[31,80,148],"using":[32,62],"efficient":[34],"spatiotemporal":[35],"detection":[37,42,136],"framework.":[38],"The":[39],"motion":[40,54,60,84],"in":[43,115,149],"most":[44],"existing":[45],"methods":[46],"unstable":[48],"computationally":[50],"expensive.":[51],"Avoiding":[52],"calculating":[53],"explicitly,":[55],"the":[56,63,91,112,127,143,146],"proposed":[57,82,101,147],"framework":[58],"generates":[59],"saliency":[61,87,94],"rank":[64],"deficiency":[65],"of":[66,145],"grayscale":[67],"gradient":[68],"tensors.":[69],"To":[70],"address":[71,131],"ill-posed":[73],"weight":[74],"determination":[75],"problem,":[76],"adaptive":[78],"fusion":[79],"spatial":[86],"integration":[88],"by":[89,102],"highlighting":[90],"more":[92],"reliable":[93],"maps.":[95],"An":[96],"attention-drive":[97],"matching":[98,122],"strategy":[99,123],"converting":[103],"values":[105],"to":[106,130],"importance":[107],"factors,":[108],"which":[109],"subsequently":[110],"boost":[111],"attended":[113],"regions":[114],"region-based":[116],"A":[119],"global":[120],"feature-based":[121],"also":[125],"included":[126],"strategy,":[129],"cases":[132],"where":[133],"visual":[134],"less":[138],"applicable.":[139],"Experiment":[140],"results":[141],"demonstrate":[142],"advantages":[144]},"counts_by_year":[{"year":2014,"cited_by_count":3},{"year":2012,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
