{"id":"https://openalex.org/W2990052897","doi":"https://doi.org/10.1109/avss.2019.8909868","title":"Spatio-Temporal Feature Extraction and Distance Metric Learning for Unconstrained Action Recognition","display_name":"Spatio-Temporal Feature Extraction and Distance Metric Learning for Unconstrained Action Recognition","publication_year":2019,"publication_date":"2019-09-01","ids":{"openalex":"https://openalex.org/W2990052897","doi":"https://doi.org/10.1109/avss.2019.8909868","mag":"2990052897"},"language":"en","primary_location":{"id":"doi:10.1109/avss.2019.8909868","is_oa":false,"landing_page_url":"https://doi.org/10.1109/avss.2019.8909868","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 16th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)","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/A5015974442","display_name":"Yongsang Yoon","orcid":"https://orcid.org/0000-0002-9806-0305"},"institutions":[{"id":"https://openalex.org/I39534123","display_name":"Gwangju Institute of Science and Technology","ror":"https://ror.org/024kbgz78","country_code":"KR","type":"education","lineage":["https://openalex.org/I39534123"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Yongsang Yoon","raw_affiliation_strings":["Gwangju Institute of Science and Technology (GIST), Gwangju, South Korea"],"affiliations":[{"raw_affiliation_string":"Gwangju Institute of Science and Technology (GIST), Gwangju, South Korea","institution_ids":["https://openalex.org/I39534123"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101783265","display_name":"Jongmin Yu","orcid":"https://orcid.org/0000-0002-0718-9948"},"institutions":[{"id":"https://openalex.org/I205640436","display_name":"Curtin University","ror":"https://ror.org/02n415q13","country_code":"AU","type":"education","lineage":["https://openalex.org/I205640436"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Jongmin Yu","raw_affiliation_strings":["Curtin University, Perth, Western Australia, Australia"],"affiliations":[{"raw_affiliation_string":"Curtin University, Perth, Western Australia, Australia","institution_ids":["https://openalex.org/I205640436"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056743652","display_name":"Moongu Jeon","orcid":"https://orcid.org/0000-0002-2775-7789"},"institutions":[{"id":"https://openalex.org/I39534123","display_name":"Gwangju Institute of Science and Technology","ror":"https://ror.org/024kbgz78","country_code":"KR","type":"education","lineage":["https://openalex.org/I39534123"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Moongu Jeon","raw_affiliation_strings":["Gwangju Institute of Science and Technology (GIST), Gwangju, South Korea"],"affiliations":[{"raw_affiliation_string":"Gwangju Institute of Science and Technology (GIST), Gwangju, South Korea","institution_ids":["https://openalex.org/I39534123"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5015974442"],"corresponding_institution_ids":["https://openalex.org/I39534123"],"apc_list":null,"apc_paid":null,"fwci":0.1012,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.45749473,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":93},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"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":0.9948999881744385,"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":0.9926000237464905,"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/discriminative-model","display_name":"Discriminative model","score":0.8843530416488647},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7527751326560974},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.7227666974067688},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7135580778121948},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6835706830024719},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6272258758544922},{"id":"https://openalex.org/keywords/action-recognition","display_name":"Action recognition","score":0.6136926412582397},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5760985612869263},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.45839962363243103},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.44522330164909363},{"id":"https://openalex.org/keywords/identity","display_name":"Identity (music)","score":0.4114992618560791},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.37542757391929626},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.22244718670845032},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.06601080298423767}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8843530416488647},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7527751326560974},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.7227666974067688},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7135580778121948},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6835706830024719},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6272258758544922},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.6136926412582397},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5760985612869263},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.45839962363243103},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.44522330164909363},{"id":"https://openalex.org/C2778355321","wikidata":"https://www.wikidata.org/wiki/Q17079427","display_name":"Identity (music)","level":2,"score":0.4114992618560791},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.37542757391929626},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.22244718670845032},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.06601080298423767},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/avss.2019.8909868","is_oa":false,"landing_page_url":"https://doi.org/10.1109/avss.2019.8909868","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 16th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7599999904632568}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W24089286","https://openalex.org/W1917989004","https://openalex.org/W1949778830","https://openalex.org/W2016053056","https://openalex.org/W2018459374","https://openalex.org/W2020163092","https://openalex.org/W2036313666","https://openalex.org/W2074604714","https://openalex.org/W2096733369","https://openalex.org/W2105101328","https://openalex.org/W2126579184","https://openalex.org/W2153579005","https://openalex.org/W2156303437","https://openalex.org/W2175640409","https://openalex.org/W2235034809","https://openalex.org/W2511556322","https://openalex.org/W2556024076","https://openalex.org/W2559833261","https://openalex.org/W2580899942","https://openalex.org/W2604128149","https://openalex.org/W2619947201","https://openalex.org/W2736596806","https://openalex.org/W2750183885","https://openalex.org/W2913926115","https://openalex.org/W2962852931","https://openalex.org/W2963446712","https://openalex.org/W2963689837","https://openalex.org/W2963886665","https://openalex.org/W2964191259","https://openalex.org/W2964339532","https://openalex.org/W3099206234","https://openalex.org/W3102616566","https://openalex.org/W4294170691","https://openalex.org/W6682691769","https://openalex.org/W6682864246"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2761785940","https://openalex.org/W1482209366","https://openalex.org/W2110523656","https://openalex.org/W2182357018"],"abstract_inverted_index":{"In":[0],"this":[1],"work,":[2],"we":[3],"proposed":[4,51,104],"a":[5,36,73],"framework":[6,52,105],"for":[7],"zero-shot":[8],"action":[9,23,32,109],"recognition":[10,33,110],"with":[11],"spatio-temporal":[12],"feature":[13],"(ST-features)":[14],"in":[15,46],"order":[16],"to":[17,39,88],"address":[18],"the":[19,30,47,80,84,103,113],"problem":[20],"of":[21,54],"unconstrained":[22,114],"recognition.":[24],"It":[25],"is":[26],"more":[27],"challenging":[28],"than":[29],"constrained":[31],"problem,":[34],"since":[35],"model":[37,60,68,82],"has":[38],"recognize":[40],"actions":[41],"which":[42],"do":[43],"not":[44],"appear":[45],"training":[48],"step.":[49],"The":[50,65,98],"consists":[53],"two":[55],"models:":[56],"1)":[57],"ST-feature":[58,66],"extraction":[59,67],"and":[61],"2)":[62],"verification":[63,81],"model.":[64],"extracts":[69],"discriminative":[70],"ST-features":[71],"from":[72],"given":[74],"video":[75],"clip.":[76],"With":[77],"these":[78],"features,":[79],"computes":[83],"similarity":[85],"between":[86],"them":[87],"examine":[89],"class-identity":[90],"whether":[91],"their":[92],"classes":[93],"are":[94],"identical":[95],"or":[96],"not.":[97],"experimental":[99],"results":[100],"show":[101],"that":[102],"can":[106],"outperform":[107],"other":[108],"methods":[111],"under":[112],"condition.":[115]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
