{"id":"https://openalex.org/W2029722532","doi":"https://doi.org/10.1109/siu.2012.6204646","title":"Recognition of complex human activities by using sequential pyramid matching","display_name":"Recognition of complex human activities by using sequential pyramid matching","publication_year":2012,"publication_date":"2012-04-01","ids":{"openalex":"https://openalex.org/W2029722532","doi":"https://doi.org/10.1109/siu.2012.6204646","mag":"2029722532"},"language":"en","primary_location":{"id":"doi:10.1109/siu.2012.6204646","is_oa":false,"landing_page_url":"https://doi.org/10.1109/siu.2012.6204646","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 20th Signal Processing and Communications Applications Conference (SIU)","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/A5015174844","display_name":"Ayta\u00e7 \u00c7avent","orcid":null},"institutions":[{"id":"https://openalex.org/I2799978770","display_name":"X-Fab (Germany)","ror":"https://ror.org/030bh9196","country_code":"DE","type":"company","lineage":["https://openalex.org/I2799978770"]},{"id":"https://openalex.org/I66514158","display_name":"Hacettepe University","ror":"https://ror.org/04kwvgz42","country_code":"TR","type":"education","lineage":["https://openalex.org/I66514158"]}],"countries":["DE","TR"],"is_corresponding":false,"raw_author_name":"Ayta\u00e7 \u00c7avent","raw_affiliation_strings":["Bilgisayar M&#x00FC;hendisli&#x011F;i B&#x00F6;l&#x00FC;m&#x00FC;, Hacettepe &#x00DC;niversitesi, Turkey","Bilgisayar M\u00fchendisli\u011fi B\u00f6l\u00fcm\u00fc, Hacettepe \u00dcniversitesi, Turkey"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bilgisayar M&#x00FC;hendisli&#x011F;i B&#x00F6;l&#x00FC;m&#x00FC;, Hacettepe &#x00DC;niversitesi, Turkey","institution_ids":["https://openalex.org/I2799978770"]},{"raw_affiliation_string":"Bilgisayar M\u00fchendisli\u011fi B\u00f6l\u00fcm\u00fc, Hacettepe \u00dcniversitesi, Turkey","institution_ids":["https://openalex.org/I66514158"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079878414","display_name":"Nazl\u0131 \u0130k\u0307izler \u010ain\u1e03i\u015f","orcid":null},"institutions":[{"id":"https://openalex.org/I2799978770","display_name":"X-Fab (Germany)","ror":"https://ror.org/030bh9196","country_code":"DE","type":"company","lineage":["https://openalex.org/I2799978770"]},{"id":"https://openalex.org/I66514158","display_name":"Hacettepe University","ror":"https://ror.org/04kwvgz42","country_code":"TR","type":"education","lineage":["https://openalex.org/I66514158"]}],"countries":["DE","TR"],"is_corresponding":false,"raw_author_name":"Nazl\u0131 \u0130kizler Cinbi\u015f","raw_affiliation_strings":["Bilgisayar M&#x00FC;hendisli&#x011F;i B&#x00F6;l&#x00FC;m&#x00FC;, Hacettepe &#x00DC;niversitesi, Turkey","Bilgisayar M\u00fchendisli\u011fi B\u00f6l\u00fcm\u00fc, Hacettepe \u00dcniversitesi, Turkey"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bilgisayar M&#x00FC;hendisli&#x011F;i B&#x00F6;l&#x00FC;m&#x00FC;, Hacettepe &#x00DC;niversitesi, Turkey","institution_ids":["https://openalex.org/I2799978770"]},{"raw_affiliation_string":"Bilgisayar M\u00fchendisli\u011fi B\u00f6l\u00fcm\u00fc, Hacettepe \u00dcniversitesi, Turkey","institution_ids":["https://openalex.org/I66514158"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"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":0.9991000294685364,"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/T10331","display_name":"Video Surveillance and Tracking Methods","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"}}],"keywords":[{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.8021087646484375},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.7199277281761169},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7067797183990479},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6367310285568237},{"id":"https://openalex.org/keywords/action-recognition","display_name":"Action recognition","score":0.5642011761665344},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5507977604866028},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.5357073545455933},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.45913106203079224},{"id":"https://openalex.org/keywords/activity-recognition","display_name":"Activity recognition","score":0.45560210943222046},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.4544837474822998},{"id":"https://openalex.org/keywords/point-of-interest","display_name":"Point of interest","score":0.44581156969070435},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34180647134780884},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.333298921585083},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.18264225125312805},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16764923930168152}],"concepts":[{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.8021087646484375},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.7199277281761169},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7067797183990479},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6367310285568237},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.5642011761665344},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5507977604866028},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.5357073545455933},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.45913106203079224},{"id":"https://openalex.org/C121687571","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity recognition","level":2,"score":0.45560210943222046},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.4544837474822998},{"id":"https://openalex.org/C150140777","wikidata":"https://www.wikidata.org/wiki/Q960648","display_name":"Point of interest","level":2,"score":0.44581156969070435},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34180647134780884},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.333298921585083},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.18264225125312805},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16764923930168152},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/siu.2012.6204646","is_oa":false,"landing_page_url":"https://doi.org/10.1109/siu.2012.6204646","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 20th Signal Processing and Communications Applications Conference (SIU)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.5199999809265137,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1498368596","https://openalex.org/W1558751150","https://openalex.org/W1993229407","https://openalex.org/W2020163092","https://openalex.org/W2096691797","https://openalex.org/W2119799051","https://openalex.org/W2134380836","https://openalex.org/W2154346517","https://openalex.org/W2162915993","https://openalex.org/W2163292664","https://openalex.org/W2165715280","https://openalex.org/W6630009274","https://openalex.org/W6633532994"],"related_works":["https://openalex.org/W3195649134","https://openalex.org/W2281498195","https://openalex.org/W2107628111","https://openalex.org/W4249847449","https://openalex.org/W2394004323","https://openalex.org/W2017526120","https://openalex.org/W2053928191","https://openalex.org/W1975325338","https://openalex.org/W3181401746","https://openalex.org/W2982423860"],"abstract_inverted_index":{"Human":[0],"action":[1,60],"recognition":[2,109,114],"is":[3,16,103],"a":[4,56,94],"topic":[5],"of":[6,13,39,50,78,85],"increasing":[7],"interest":[8,45,81],"in":[9,106],"recent":[10],"years.":[11],"Most":[12],"the":[14,48,76,79,99,110],"work":[15],"focused":[17],"on":[18,59,93],"actions":[19,40],"that":[20,105],"have":[21,53],"simple,":[22],"periodic":[23],"structure":[24],"such":[25],"as":[26],"walking,":[27],"running":[28],"and":[29,47,83],"hugging,":[30],"but":[31],"our":[32],"everyday":[33],"life":[34],"contains":[35],"very":[36],"different":[37],"types":[38],"with":[41],"challenging":[42,95],"problems.":[43],"Space-time":[44],"points":[46,82],"bag":[49,84],"words":[51,86],"approach":[52,87,112],"been":[54],"shown":[55,104],"good":[57],"performance":[58,77],"recognition.":[61],"For":[62],"more":[63],"complex":[64,107],"activities,":[65],"finer":[66],"representations":[67],"must":[68],"be":[69],"employed.":[70],"In":[71],"this":[72],"article,":[73],"we":[74],"present":[75],"space-time":[80],"by":[88],"using":[89],"sequential":[90],"histogram":[91],"pyramid":[92],"dataset.":[96],"According":[97],"to":[98],"test":[100],"results,":[101],"it":[102],"activity":[108],"proposed":[111],"increases":[113],"performance.":[115]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
