{"id":"https://openalex.org/W2155983176","doi":"https://doi.org/10.1109/iccv.2007.4408865","title":"A Scalable Approach to Activity Recognition based on Object Use","display_name":"A Scalable Approach to Activity Recognition based on Object Use","publication_year":2007,"publication_date":"2007-01-01","ids":{"openalex":"https://openalex.org/W2155983176","doi":"https://doi.org/10.1109/iccv.2007.4408865","mag":"2155983176"},"language":"en","primary_location":{"id":"doi:10.1109/iccv.2007.4408865","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2007.4408865","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 IEEE 11th International Conference on Computer Vision","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/A5090881698","display_name":"Jianxin Wu","orcid":"https://orcid.org/0000-0002-2085-7568"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jianxin Wu","raw_affiliation_strings":["College of Computing, Georgia Institute of Technology, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computing, Georgia Institute of Technology, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046901549","display_name":"A. Osuntogun","orcid":null},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Adebola Osuntogun","raw_affiliation_strings":["College of Computing, Georgia Institute of Technology, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computing, Georgia Institute of Technology, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046665314","display_name":"Tanzeem Choudhury","orcid":"https://orcid.org/0000-0002-5952-4955"},"institutions":[{"id":"https://openalex.org/I1343180700","display_name":"Intel (United States)","ror":"https://ror.org/01ek73717","country_code":"US","type":"company","lineage":["https://openalex.org/I1343180700"]},{"id":"https://openalex.org/I58610484","display_name":"Seattle University","ror":"https://ror.org/02jqc0m91","country_code":"US","type":"education","lineage":["https://openalex.org/I58610484"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tanzeem Choudhury","raw_affiliation_strings":["Intel Research Seattle, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Intel Research Seattle, USA","institution_ids":["https://openalex.org/I1343180700","https://openalex.org/I58610484"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030096283","display_name":"Matthai Philipose","orcid":null},"institutions":[{"id":"https://openalex.org/I1343180700","display_name":"Intel (United States)","ror":"https://ror.org/01ek73717","country_code":"US","type":"company","lineage":["https://openalex.org/I1343180700"]},{"id":"https://openalex.org/I58610484","display_name":"Seattle University","ror":"https://ror.org/02jqc0m91","country_code":"US","type":"education","lineage":["https://openalex.org/I58610484"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Matthai Philipose","raw_affiliation_strings":["Intel Research Seattle, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Intel Research Seattle, USA","institution_ids":["https://openalex.org/I1343180700","https://openalex.org/I58610484"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002228469","display_name":"James M. Rehg","orcid":"https://orcid.org/0000-0003-1793-5462"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"James M. Rehg","raw_affiliation_strings":["College of Computing, Georgia Institute of Technology, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computing, Georgia Institute of Technology, USA","institution_ids":["https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":16.5557,"has_fulltext":false,"cited_by_count":325,"citation_normalized_percentile":{"value":0.99482244,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9987000226974487,"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9987000226974487,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9984999895095825,"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":0.9968000054359436,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8391111493110657},{"id":"https://openalex.org/keywords/activity-recognition","display_name":"Activity recognition","score":0.7872766256332397},{"id":"https://openalex.org/keywords/clutter","display_name":"Clutter","score":0.7556238174438477},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.6995389461517334},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6377570629119873},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6280022263526917},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.6018056273460388},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5877219438552856},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4825536608695984},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.46519577503204346},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.44428738951683044},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37147057056427}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8391111493110657},{"id":"https://openalex.org/C121687571","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity recognition","level":2,"score":0.7872766256332397},{"id":"https://openalex.org/C132094186","wikidata":"https://www.wikidata.org/wiki/Q641585","display_name":"Clutter","level":3,"score":0.7556238174438477},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.6995389461517334},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6377570629119873},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6280022263526917},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.6018056273460388},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5877219438552856},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4825536608695984},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.46519577503204346},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.44428738951683044},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37147057056427},{"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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/iccv.2007.4408865","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2007.4408865","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 IEEE 11th International Conference on Computer Vision","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.86.3668","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.86.3668","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cc.gatech.edu/grads/o/osuntogu/Publications/iccv07.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.7300000190734863,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W98188630","https://openalex.org/W1496163732","https://openalex.org/W1677409904","https://openalex.org/W1718093723","https://openalex.org/W1768921720","https://openalex.org/W1971724799","https://openalex.org/W2003637680","https://openalex.org/W2098517267","https://openalex.org/W2098782609","https://openalex.org/W2101666158","https://openalex.org/W2103658758","https://openalex.org/W2105046342","https://openalex.org/W2114701396","https://openalex.org/W2130007767","https://openalex.org/W2134266767","https://openalex.org/W2134685637","https://openalex.org/W2146136606","https://openalex.org/W2151103935","https://openalex.org/W2153746365","https://openalex.org/W2154346517","https://openalex.org/W2160517719","https://openalex.org/W2160675703","https://openalex.org/W2161029186","https://openalex.org/W2161612652","https://openalex.org/W2163739721","https://openalex.org/W2165715280","https://openalex.org/W3141200356","https://openalex.org/W6604091132","https://openalex.org/W6629812752","https://openalex.org/W6637400245","https://openalex.org/W6637837658","https://openalex.org/W6675198320","https://openalex.org/W6675583992","https://openalex.org/W6683492740"],"related_works":["https://openalex.org/W2130674020","https://openalex.org/W2093748878","https://openalex.org/W2333771223","https://openalex.org/W2120056845","https://openalex.org/W1981531423","https://openalex.org/W2035264131","https://openalex.org/W2106002764","https://openalex.org/W1579998189","https://openalex.org/W2172615727","https://openalex.org/W4387272257"],"abstract_inverted_index":{"We":[0,69,117,140,170],"propose":[1],"an":[2],"approach":[3,45,86,144],"to":[4,46,48,57,105,112,130,198],"activity":[5,136,147,213],"recognition":[6,148,178],"based":[7],"on":[8,154],"detecting":[9],"and":[10,51,89,127,137,208],"analyzing":[11],"the":[12,21,59,114,133,173,187],"sequence":[13],"of":[14,61,150,159,175,205],"objects":[15,102,165],"that":[16,64,142,172,194],"are":[17,103],"being":[18],"manipulated":[19],"by":[20],"user.":[22],"In":[23,41],"domains":[24],"such":[25],"as":[26],"cooking,":[27],"where":[28],"many":[29,49],"activities":[30,50,162,207],"involve":[31],"similar":[32],"actions,":[33],"object-use":[34],"information":[35],"can":[36,145],"be":[37,106],"a":[38,71,109,119,155],"valuable":[39],"cue.":[40],"order":[42],"for":[43,67,73,212],"this":[44],"scale":[47],"objects,":[52,95],"however,":[53],"it":[54,195],"is":[55,65,182,196],"necessary":[56],"minimize":[58],"amount":[60],"human-labeled":[62],"data":[63,129,181],"required":[66],"modeling.":[68],"describe":[70],"method":[72],"automatically":[74,199],"acquiring":[75],"object":[76,138,177,201],"models":[77,202,211],"from":[78,92,203],"video":[79,128,204],"without":[80,215],"any":[81,217],"explicit":[82,218],"human":[83,219],"supervision.":[84],"Our":[85,191],"leverages":[87],"sparse":[88],"noisy":[90],"readings":[91],"RFID":[93,126,180,188],"tagged":[94],"along":[96],"with":[97,166,179],"common-sense":[98],"knowledge":[99],"about":[100],"which":[101,124],"likely":[104,135],"used":[107],"during":[108],"given":[110],"activity,":[111],"bootstrap":[113],"learning":[115],"process.":[116],"present":[118],"dynamic":[120],"Bayesian":[121],"network":[122],"model":[123],"combines":[125],"jointly":[131],"infer":[132],"most":[134],"labels.":[139],"demonstrate":[141],"our":[143],"achieve":[146],"rates":[149],"more":[151,184],"than":[152,186],"80%":[153],"real-world":[156],"dataset":[157],"consisting":[158],"16":[160],"household":[161,206],"involving":[163],"33":[164],"significant":[167],"background":[168],"clutter.":[169],"show":[171],"combination":[174],"visual":[176],"significantly":[183],"effective":[185],"sensor":[189],"alone.":[190],"work":[192],"demonstrates":[193],"possible":[197],"learn":[200],"employ":[209],"these":[210],"recognition,":[214],"requiring":[216],"labeling.":[220]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":14},{"year":2018,"cited_by_count":19},{"year":2017,"cited_by_count":16},{"year":2016,"cited_by_count":27},{"year":2015,"cited_by_count":33},{"year":2014,"cited_by_count":26},{"year":2013,"cited_by_count":24},{"year":2012,"cited_by_count":31}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}