{"id":"https://openalex.org/W2791092259","doi":"https://doi.org/10.1109/rcar.2017.8311837","title":"Pseudo trajectories eliminating and pyramid clustering: Optimizing dense trajectories for action recognition","display_name":"Pseudo trajectories eliminating and pyramid clustering: Optimizing dense trajectories for action recognition","publication_year":2017,"publication_date":"2017-07-01","ids":{"openalex":"https://openalex.org/W2791092259","doi":"https://doi.org/10.1109/rcar.2017.8311837","mag":"2791092259"},"language":"en","primary_location":{"id":"doi:10.1109/rcar.2017.8311837","is_oa":false,"landing_page_url":"https://doi.org/10.1109/rcar.2017.8311837","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Real-time Computing and Robotics (RCAR)","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/A5074964641","display_name":"Yupeng Zhan","orcid":null},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yupeng Zhan","raw_affiliation_strings":["Department of Electronics & Information Engineering, South China University of Technology (SCUT), Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"Department of Electronics & Information Engineering, South China University of Technology (SCUT), Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047427624","display_name":"Lihong Ma","orcid":"https://orcid.org/0000-0002-2732-6030"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lihong Ma","raw_affiliation_strings":["Department of Electronics & Information Engineering, South China University of Technology (SCUT), Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"Department of Electronics & Information Engineering, South China University of Technology (SCUT), Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023134878","display_name":"Chunling Yang","orcid":"https://orcid.org/0000-0001-7801-9519"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunling Yang","raw_affiliation_strings":["Department of Electronics & Information Engineering, South China University of Technology (SCUT), Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"Department of Electronics & Information Engineering, South China University of Technology (SCUT), Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5074964641"],"corresponding_institution_ids":["https://openalex.org/I90610280"],"apc_list":null,"apc_paid":null,"fwci":0.091,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.51013023,"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":"62","last_page":"67"},"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/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"}},{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":0.996999979019165,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7883545160293579},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.681468665599823},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.645807147026062},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6369092464447021},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.5206966996192932},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.5060426592826843},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4904758632183075},{"id":"https://openalex.org/keywords/action-recognition","display_name":"Action recognition","score":0.4706524908542633},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4639093279838562},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.4254691004753113},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.4200739860534668},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.4187930226325989},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2041022777557373},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.18359264731407166},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.15662848949432373}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7883545160293579},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.681468665599823},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.645807147026062},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6369092464447021},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.5206966996192932},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.5060426592826843},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4904758632183075},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.4706524908542633},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4639093279838562},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.4254691004753113},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.4200739860534668},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.4187930226325989},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2041022777557373},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.18359264731407166},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.15662848949432373},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/rcar.2017.8311837","is_oa":false,"landing_page_url":"https://doi.org/10.1109/rcar.2017.8311837","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Real-time Computing and Robotics (RCAR)","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":20,"referenced_works":["https://openalex.org/W1973166425","https://openalex.org/W2007815619","https://openalex.org/W2027510893","https://openalex.org/W2032266162","https://openalex.org/W2034328688","https://openalex.org/W2044966771","https://openalex.org/W2068611653","https://openalex.org/W2097437738","https://openalex.org/W2105101328","https://openalex.org/W2108333036","https://openalex.org/W2119799051","https://openalex.org/W2126574503","https://openalex.org/W2142194269","https://openalex.org/W2143215648","https://openalex.org/W2146634731","https://openalex.org/W2165715280","https://openalex.org/W2290415046","https://openalex.org/W2533739470","https://openalex.org/W3141200356","https://openalex.org/W4249279051"],"related_works":["https://openalex.org/W1542224353","https://openalex.org/W2125652721","https://openalex.org/W1661087619","https://openalex.org/W1540371141","https://openalex.org/W4231274751","https://openalex.org/W1549363203","https://openalex.org/W2154063878","https://openalex.org/W2556012038","https://openalex.org/W1489772951","https://openalex.org/W2116854923"],"abstract_inverted_index":{"Motion":[0,47],"path":[1],"methods,":[2],"especially":[3],"for":[4,10,56],"dense":[5,79],"trajectories,":[6],"have":[7],"showed":[8],"effectiveness":[9],"action":[11],"recognition.":[12],"To":[13],"select":[14],"the":[15,29,61,87],"most":[16],"representative":[17],"trajectories":[18,31,80],"of":[19,63,67],"motion":[20],"objects,":[21],"a":[22],"novel":[23],"approach":[24],"is":[25],"presented":[26],"to":[27,82],"eliminate":[28],"pseudo":[30],"generated":[32],"by":[33,69],"background":[34],"disturbance,":[35],"camera":[36],"shake":[37],"and":[38,85],"failure":[39],"tracking.":[40],"Benefits":[41],"in":[42,65],"our":[43,76],"method":[44,77],"include:":[45],"(i)":[46],"region":[48],"boosting":[49],"compensating":[50],"object":[51],"shift.":[52],"(ii)":[53],"Differential":[54],"thresholding":[55],"rapid":[57],"computation.":[58],"(iii)":[59],"Strengthening":[60],"independence":[62],"words":[64],"Bag":[66],"Features":[68],"pyramid":[70],"clustering.":[71],"Experimental":[72],"results":[73],"prove":[74],"that":[75],"selects":[78],"belonging":[81],"objects":[83],"effectively":[84],"improves":[86],"recognition":[88],"accuracy.":[89]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
