{"id":"https://openalex.org/W1981739160","doi":"https://doi.org/10.1109/icip.2010.5653768","title":"Making full use of spatial-temporal interest points: An AdaBoost approach for action recognition","display_name":"Making full use of spatial-temporal interest points: An AdaBoost approach for action recognition","publication_year":2010,"publication_date":"2010-09-01","ids":{"openalex":"https://openalex.org/W1981739160","doi":"https://doi.org/10.1109/icip.2010.5653768","mag":"1981739160"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2010.5653768","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2010.5653768","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE International Conference on Image Processing","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/A5028940427","display_name":"Xunshi Yan","orcid":"https://orcid.org/0000-0002-0372-7120"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xunshi Yan","raw_affiliation_strings":["Tsinghua National Laboratory of Information Science and Technology (TNList), Department of Automation, Tsinghua University, Beijing, China","[Tsinghua National Laboratory for Information Science and Technology (TNList), China]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua National Laboratory of Information Science and Technology (TNList), Department of Automation, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"[Tsinghua National Laboratory for Information Science and Technology (TNList), China]","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113653028","display_name":"Yupin Luo","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yupin Luo","raw_affiliation_strings":["Tsinghua National Laboratory of Information Science and Technology (TNList), Department of Automation, Tsinghua University, Beijing, China","[Tsinghua National Laboratory for Information Science and Technology (TNList), China]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua National Laboratory of Information Science and Technology (TNList), Department of Automation, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"[Tsinghua National Laboratory for Information Science and Technology (TNList), China]","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4677","last_page":"4680"},"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/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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":0.9976000189781189,"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/adaboost","display_name":"AdaBoost","score":0.7547669410705566},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7093849182128906},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6889113187789917},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.6493180394172668},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6206305623054504},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6016273498535156},{"id":"https://openalex.org/keywords/spatial-relation","display_name":"Spatial relation","score":0.4980173110961914},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.48082029819488525},{"id":"https://openalex.org/keywords/action-recognition","display_name":"Action recognition","score":0.4616725444793701},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.44333750009536743},{"id":"https://openalex.org/keywords/point-of-interest","display_name":"Point of interest","score":0.42809751629829407},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.2384113073348999},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15833592414855957},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.1296057105064392},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.10340616106987},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.07378488779067993},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.061132997274398804}],"concepts":[{"id":"https://openalex.org/C141404830","wikidata":"https://www.wikidata.org/wiki/Q2823869","display_name":"AdaBoost","level":3,"score":0.7547669410705566},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7093849182128906},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6889113187789917},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.6493180394172668},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6206305623054504},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6016273498535156},{"id":"https://openalex.org/C27511587","wikidata":"https://www.wikidata.org/wiki/Q2178623","display_name":"Spatial relation","level":2,"score":0.4980173110961914},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.48082029819488525},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.4616725444793701},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.44333750009536743},{"id":"https://openalex.org/C150140777","wikidata":"https://www.wikidata.org/wiki/Q960648","display_name":"Point of interest","level":2,"score":0.42809751629829407},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.2384113073348999},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15833592414855957},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.1296057105064392},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.10340616106987},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.07378488779067993},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.061132997274398804},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2010.5653768","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2010.5653768","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE International Conference on Image Processing","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":15,"referenced_works":["https://openalex.org/W2032210760","https://openalex.org/W2034328688","https://openalex.org/W2096691069","https://openalex.org/W2106918732","https://openalex.org/W2114016557","https://openalex.org/W2119799051","https://openalex.org/W2130843763","https://openalex.org/W2158169396","https://openalex.org/W2158634668","https://openalex.org/W2161969291","https://openalex.org/W2164598857","https://openalex.org/W2165715280","https://openalex.org/W2533739470","https://openalex.org/W3141200356","https://openalex.org/W4249279051"],"related_works":["https://openalex.org/W2571042389","https://openalex.org/W2752217129","https://openalex.org/W2159209200","https://openalex.org/W2108748717","https://openalex.org/W2726222394","https://openalex.org/W2989079813","https://openalex.org/W1829185492","https://openalex.org/W2143484882","https://openalex.org/W2941155331","https://openalex.org/W1981739160"],"abstract_inverted_index":{"Although":[0],"spatial-temporal":[1,48,54],"interest":[2],"points":[3],"(STIPs)":[4],"with":[5],"bag":[6,46,52],"of":[7,47,53],"words":[8,49,55],"strategy":[9],"have":[10],"achieved":[11],"success":[12],"in":[13,41],"action":[14],"recognition,":[15],"they":[16],"lose":[17],"much":[18],"information":[19],"during":[20],"forming":[21],"histograms,":[22],"especially":[23],"the":[24,58],"relations":[25,40],"among":[26],"STIPs.":[27],"We":[28],"propose":[29],"to":[30,37,43,63],"use":[31],"effective":[32],"human":[33],"body":[34],"regions":[35],"(EHBRs)":[36],"find":[38],"these":[39],"order":[42],"compensate":[44],"for":[45],"(BOW).":[50],"Combining":[51],"and":[56,76],"EHBRs,":[57],"AdaBoost":[59],"approach":[60,74],"is":[61],"used":[62],"achieve":[64],"high":[65],"accuracy.":[66],"Experiments":[67],"on":[68],"benchmark":[69],"dataset":[70],"KTH":[71],"verify":[72],"our":[73],"effectiveness":[75],"efficiency.":[77]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":2},{"year":2012,"cited_by_count":4}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
