{"id":"https://openalex.org/W2015822910","doi":"https://doi.org/10.1145/2502081.2508123","title":"Human action recognition by fast dense trajectories","display_name":"Human action recognition by fast dense trajectories","publication_year":2013,"publication_date":"2013-10-21","ids":{"openalex":"https://openalex.org/W2015822910","doi":"https://doi.org/10.1145/2502081.2508123","mag":"2015822910"},"language":"en","primary_location":{"id":"doi:10.1145/2502081.2508123","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2502081.2508123","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 21st ACM international conference on Multimedia","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/A5066043158","display_name":"Zongbo Hao","orcid":null},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zongbo Hao","raw_affiliation_strings":["University of Electronic Science and Technology of China, Chengdu, China","University of Electronic Science & Technology of China, ChengDu, China#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]},{"raw_affiliation_string":"University of Electronic Science & Technology of China, ChengDu, China#TAB#","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067368513","display_name":"Qianni Zhang","orcid":"https://orcid.org/0000-0001-7685-2187"},"institutions":[{"id":"https://openalex.org/I166337079","display_name":"Queen Mary University of London","ror":"https://ror.org/026zzn846","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I166337079"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Qianni Zhang","raw_affiliation_strings":["Queen Mary, University of London, London, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Queen Mary, University of London, London, United Kingdom","institution_ids":["https://openalex.org/I166337079"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069006688","display_name":"Ebroul Ezquierdo","orcid":null},"institutions":[{"id":"https://openalex.org/I166337079","display_name":"Queen Mary University of London","ror":"https://ror.org/026zzn846","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I166337079"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Ebroul Ezquierdo","raw_affiliation_strings":["Queen Mary, University of London, London, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Queen Mary, University of London, London, United Kingdom","institution_ids":["https://openalex.org/I166337079"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075116817","display_name":"Nan Sang","orcid":"https://orcid.org/0000-0002-5735-2301"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Nan Sang","raw_affiliation_strings":["University of Electronic Science and Technology of China, Chengdu, China","University of Electronic Science & Technology of China, ChengDu, China#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]},{"raw_affiliation_string":"University of Electronic Science & Technology of China, ChengDu, China#TAB#","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8315,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.74646974,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"377","last_page":"380"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":1.0,"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":1.0,"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":0.9944000244140625,"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"}},{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":0.9934999942779541,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8173571825027466},{"id":"https://openalex.org/keywords/action-recognition","display_name":"Action recognition","score":0.7546509504318237},{"id":"https://openalex.org/keywords/scale-invariant-feature-transform","display_name":"Scale-invariant feature transform","score":0.7459702491760254},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7370291352272034},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5893644094467163},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.5757426619529724},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5558051466941833},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.541221559047699},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5111091732978821},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.46274593472480774},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.4109201729297638}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8173571825027466},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.7546509504318237},{"id":"https://openalex.org/C61265191","wikidata":"https://www.wikidata.org/wiki/Q767770","display_name":"Scale-invariant feature transform","level":3,"score":0.7459702491760254},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7370291352272034},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5893644094467163},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.5757426619529724},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5558051466941833},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.541221559047699},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5111091732978821},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.46274593472480774},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.4109201729297638},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","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},{"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/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},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2502081.2508123","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2502081.2508123","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 21st ACM international conference on Multimedia","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":19,"referenced_works":["https://openalex.org/W1534763723","https://openalex.org/W2010399676","https://openalex.org/W2020163092","https://openalex.org/W2064851185","https://openalex.org/W2099806072","https://openalex.org/W2106996050","https://openalex.org/W2116931983","https://openalex.org/W2118572719","https://openalex.org/W2118585731","https://openalex.org/W2126574503","https://openalex.org/W2129620337","https://openalex.org/W2138232383","https://openalex.org/W2158169396","https://openalex.org/W2165605600","https://openalex.org/W2533739470","https://openalex.org/W3001645704","https://openalex.org/W3141200356","https://openalex.org/W6602469948","https://openalex.org/W6835133323"],"related_works":["https://openalex.org/W2058965144","https://openalex.org/W2164382479","https://openalex.org/W98480971","https://openalex.org/W2150291671","https://openalex.org/W2027972911","https://openalex.org/W2146343568","https://openalex.org/W2013643406","https://openalex.org/W2049930962","https://openalex.org/W2108333036","https://openalex.org/W4285215860"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,47,61],"propose":[4],"the":[5,35,45,52,57,63,76,79,103],"fast":[6,19],"dense":[7,38,104],"trajectories":[8,15,39,50,105],"algorithm":[9],"for":[10,70],"human":[11,85],"action":[12,72,88],"recognition.":[13],"Dense":[14],"are":[16],"robust":[17],"to":[18,66,111],"irregular":[20],"motions":[21],"and":[22,60,87,109],"outperform":[23],"other":[24],"state-of-the-art":[25],"descriptors":[26],"such":[27],"as":[28],"KLT":[29],"tracker":[30],"or":[31],"SIFT":[32],"descriptors.":[33],"However,":[34],"use":[36,62],"of":[37,81],"is":[40],"time":[41],"consuming.":[42],"To":[43],"improve":[44],"efficiency,":[46],"extract":[48],"feature":[49],"in":[51,56,92,107],"ROI":[53],"rather":[54],"than":[55],"whole":[58],"frames,":[59],"temporal":[64],"pyramids":[65],"achieve":[67],"adaptable":[68,110],"mechanism":[69],"different":[71,112],"speed.":[73,113],"We":[74],"evaluate":[75],"method":[77],"on":[78],"dataset":[80],"Huawei/3DLife":[82],"--":[83],"3D":[84],"reconstruction":[86],"recognition":[89],"Grand":[90],"Challenge":[91],"ACM":[93],"Multimedia":[94],"2013.":[95],"Experimental":[96],"results":[97],"show":[98],"a":[99],"significant":[100],"improvement":[101],"over":[102],"descriptor":[106],"real-time,":[108]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}