{"id":"https://openalex.org/W1981936999","doi":"https://doi.org/10.1109/icra.2012.6224702","title":"A connectionist-based approach for human action identification","display_name":"A connectionist-based approach for human action identification","publication_year":2012,"publication_date":"2012-05-01","ids":{"openalex":"https://openalex.org/W1981936999","doi":"https://doi.org/10.1109/icra.2012.6224702","mag":"1981936999"},"language":"en","primary_location":{"id":"doi:10.1109/icra.2012.6224702","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra.2012.6224702","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE International Conference on Robotics and Automation","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/A5029787567","display_name":"Rami Alazrai","orcid":"https://orcid.org/0000-0002-1296-0231"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Rami Alazrai","raw_affiliation_strings":["School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA","School of Electrical and Computer Engineering, Purdue University,  West Lafayette, IN 47907, U.S.A"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]},{"raw_affiliation_string":"School of Electrical and Computer Engineering, Purdue University,  West Lafayette, IN 47907, U.S.A","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026925435","display_name":"C. S. George Lee","orcid":"https://orcid.org/0000-0002-5610-0671"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"C. S. George Lee","raw_affiliation_strings":["School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA","School of Electrical and Computer Engineering, Purdue University,  West Lafayette, IN 47907, U.S.A"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]},{"raw_affiliation_string":"School of Electrical and Computer Engineering, Purdue University,  West Lafayette, IN 47907, U.S.A","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5029787567"],"corresponding_institution_ids":["https://openalex.org/I219193219"],"apc_list":null,"apc_paid":null,"fwci":0.5491,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.66154563,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1212","last_page":"1217"},"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":0.9993000030517578,"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":0.9977999925613403,"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":0.7854688763618469},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7182451486587524},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.510475754737854},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.4817931056022644},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4662771224975586},{"id":"https://openalex.org/keywords/connectionism","display_name":"Connectionism","score":0.44095349311828613},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4109418988227844},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.4109169542789459},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4089372456073761}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7854688763618469},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7182451486587524},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.510475754737854},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.4817931056022644},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4662771224975586},{"id":"https://openalex.org/C8521452","wikidata":"https://www.wikidata.org/wiki/Q203790","display_name":"Connectionism","level":3,"score":0.44095349311828613},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4109418988227844},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.4109169542789459},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4089372456073761},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/icra.2012.6224702","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra.2012.6224702","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE International Conference on Robotics and Automation","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":25,"referenced_works":["https://openalex.org/W1529008516","https://openalex.org/W1542475657","https://openalex.org/W1910567995","https://openalex.org/W1983705368","https://openalex.org/W2016589492","https://openalex.org/W2022585102","https://openalex.org/W2034328688","https://openalex.org/W2035866593","https://openalex.org/W2079100816","https://openalex.org/W2087946919","https://openalex.org/W2110142955","https://openalex.org/W2110485445","https://openalex.org/W2115213191","https://openalex.org/W2124635854","https://openalex.org/W2142194269","https://openalex.org/W2154683974","https://openalex.org/W2156135524","https://openalex.org/W2161969291","https://openalex.org/W2162915993","https://openalex.org/W2165760905","https://openalex.org/W2533739470","https://openalex.org/W4249279051","https://openalex.org/W4254816979","https://openalex.org/W6632542820","https://openalex.org/W6676671045"],"related_works":["https://openalex.org/W4205841273","https://openalex.org/W4205525690","https://openalex.org/W1761388607","https://openalex.org/W1997922073","https://openalex.org/W2604685715","https://openalex.org/W2412160900","https://openalex.org/W2136453575","https://openalex.org/W1596913645","https://openalex.org/W1024498263","https://openalex.org/W2504816413"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,12,24,154],"hierarchal,":[4],"two-layer,":[5],"connectionist-based":[6],"human-action":[7,124,128,149],"recognition":[8,150,156],"system":[9],"(CHARS)":[10],"as":[11],"first":[13,21],"step":[14],"towards":[15],"developing":[16],"socially":[17],"intelligent":[18],"robots.":[19],"The":[20,77,138],"layer":[22,45],"is":[23,69],"K-nearest":[25],"neighbor":[26],"(K-NN)":[27],"classifier":[28],"that":[29,53],"categorizes":[30],"human":[31],"actions":[32],"into":[33],"two":[34,48],"classes":[35],"based":[36],"on":[37],"the":[38,43,81,93,104,107,111,127],"existence":[39],"of":[40,47,62,64,83,106,113],"locomotion,":[41],"and":[42,74,95,110,126,152],"second":[44],"consists":[46],"multi-layer":[49],"recurrent":[50],"neural":[51],"networks":[52],"distinguish":[54],"between":[55],"subclasses":[56],"within":[57],"each":[58],"class.":[59],"A":[60,120],"pyramid":[61],"histograms":[63],"oriented":[65],"gradients":[66],"(PHOG)":[67],"descriptor":[68,79],"proposed":[70,108,139],"for":[71,92,135],"extracting":[72],"local":[73],"spatial":[75],"features.":[76],"PHOG":[78],"reduces":[80],"dimensionality":[82],"input":[84],"space":[85],"drastically,":[86],"which":[87],"results":[88],"in":[89,116],"better":[90,145],"convergence":[91],"learning":[94],"classification":[96],"processes.":[97],"Computer":[98],"simulations":[99],"were":[100,133],"conducted":[101],"to":[102,143],"illustrate":[103],"performance":[105,136],"CHARS":[109,140],"role":[112],"temporal":[114],"factor":[115],"solving":[117],"this":[118],"problem.":[119],"widely":[121],"used":[122],"KTH":[123],"database":[125],"dataset":[129],"from":[130],"our":[131],"lab":[132],"utilized":[134],"evaluation.":[137],"was":[141],"found":[142],"perform":[144],"than":[146],"other":[147],"existing":[148],"methods":[151],"achieved":[153],"95.55%":[155],"rate.":[157]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
