{"id":"https://openalex.org/W4308216826","doi":"https://doi.org/10.1109/iciscae55891.2022.9927546","title":"A Planar Object Tracking Algorithm Based on Fully Convolutional Dense Network","display_name":"A Planar Object Tracking Algorithm Based on Fully Convolutional Dense Network","publication_year":2022,"publication_date":"2022-09-23","ids":{"openalex":"https://openalex.org/W4308216826","doi":"https://doi.org/10.1109/iciscae55891.2022.9927546"},"language":"en","primary_location":{"id":"doi:10.1109/iciscae55891.2022.9927546","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iciscae55891.2022.9927546","pdf_url":null,"source":{"id":"https://openalex.org/S4363608062","display_name":"2022 IEEE 5th International Conference on Information Systems and Computer Aided Education (ICISCAE)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 5th International Conference on Information Systems and Computer Aided Education (ICISCAE)","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/A5100399763","display_name":"Shilin Liu","orcid":"https://orcid.org/0000-0002-3704-3798"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shuling Liu","raw_affiliation_strings":["Zhengzhou University,Zhengzhou,China","Zhengzhou University, Zhengzhou, China"],"affiliations":[{"raw_affiliation_string":"Zhengzhou University,Zhengzhou,China","institution_ids":["https://openalex.org/I38877650"]},{"raw_affiliation_string":"Zhengzhou University, Zhengzhou, China","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007597759","display_name":"Suinan Wen","orcid":null},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Suinan Wen","raw_affiliation_strings":["Zhengzhou University,Zhengzhou,China","Zhengzhou University, Zhengzhou, China"],"affiliations":[{"raw_affiliation_string":"Zhengzhou University,Zhengzhou,China","institution_ids":["https://openalex.org/I38877650"]},{"raw_affiliation_string":"Zhengzhou University, Zhengzhou, China","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100432734","display_name":"Peng Li","orcid":"https://orcid.org/0000-0002-7820-4412"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Li","raw_affiliation_strings":["Zhengzhou University,Zhengzhou,China","Zhengzhou University, Zhengzhou, China"],"affiliations":[{"raw_affiliation_string":"Zhengzhou University,Zhengzhou,China","institution_ids":["https://openalex.org/I38877650"]},{"raw_affiliation_string":"Zhengzhou University, Zhengzhou, China","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087499452","display_name":"Wanyu Hou","orcid":null},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wanyu Hou","raw_affiliation_strings":["Zhengzhou University,Zhengzhou,China","Zhengzhou University, Zhengzhou, China"],"affiliations":[{"raw_affiliation_string":"Zhengzhou University,Zhengzhou,China","institution_ids":["https://openalex.org/I38877650"]},{"raw_affiliation_string":"Zhengzhou University, Zhengzhou, China","institution_ids":["https://openalex.org/I38877650"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100399763"],"corresponding_institution_ids":["https://openalex.org/I38877650"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.10295166,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"37","issue":null,"first_page":"480","last_page":"487"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9998999834060669,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9998999834060669,"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/T11963","display_name":"Impact of Light on Environment and Health","score":0.9702000021934509,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental 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":0.9373999834060669,"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/ransac","display_name":"RANSAC","score":0.7904941439628601},{"id":"https://openalex.org/keywords/minimum-bounding-box","display_name":"Minimum bounding box","score":0.7348422408103943},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6968618035316467},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5837718844413757},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5703049302101135},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.545886754989624},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.46091607213020325},{"id":"https://openalex.org/keywords/scale-invariant-feature-transform","display_name":"Scale-invariant feature transform","score":0.458989679813385},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.44225937128067017},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.42112958431243896},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40934231877326965},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.37244749069213867},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.3320455551147461},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.24631693959236145}],"concepts":[{"id":"https://openalex.org/C114744707","wikidata":"https://www.wikidata.org/wiki/Q218533","display_name":"RANSAC","level":3,"score":0.7904941439628601},{"id":"https://openalex.org/C147037132","wikidata":"https://www.wikidata.org/wiki/Q6865426","display_name":"Minimum bounding box","level":3,"score":0.7348422408103943},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6968618035316467},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5837718844413757},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5703049302101135},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.545886754989624},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.46091607213020325},{"id":"https://openalex.org/C61265191","wikidata":"https://www.wikidata.org/wiki/Q767770","display_name":"Scale-invariant feature transform","level":3,"score":0.458989679813385},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.44225937128067017},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.42112958431243896},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40934231877326965},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.37244749069213867},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3320455551147461},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.24631693959236145},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iciscae55891.2022.9927546","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iciscae55891.2022.9927546","pdf_url":null,"source":{"id":"https://openalex.org/S4363608062","display_name":"2022 IEEE 5th International Conference on Information Systems and Computer Aided Education (ICISCAE)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 5th International Conference on Information Systems and Computer Aided Education (ICISCAE)","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":28,"referenced_works":["https://openalex.org/W99485931","https://openalex.org/W639708223","https://openalex.org/W1857884451","https://openalex.org/W1992047056","https://openalex.org/W2035379092","https://openalex.org/W2089217417","https://openalex.org/W2130502925","https://openalex.org/W2140804329","https://openalex.org/W2151103935","https://openalex.org/W2154889144","https://openalex.org/W2163806380","https://openalex.org/W2470394683","https://openalex.org/W2557641257","https://openalex.org/W2604763608","https://openalex.org/W2753160622","https://openalex.org/W2776035257","https://openalex.org/W2797812763","https://openalex.org/W2799058067","https://openalex.org/W2886910176","https://openalex.org/W2953303875","https://openalex.org/W2963499285","https://openalex.org/W2966759264","https://openalex.org/W3001584168","https://openalex.org/W3011524659","https://openalex.org/W6620707391","https://openalex.org/W6681968150","https://openalex.org/W6736057607","https://openalex.org/W6743661861"],"related_works":["https://openalex.org/W2912782527","https://openalex.org/W2002904063","https://openalex.org/W2559085038","https://openalex.org/W2184781617","https://openalex.org/W2724122122","https://openalex.org/W2410884360","https://openalex.org/W2032794652","https://openalex.org/W2613823046","https://openalex.org/W4251240031","https://openalex.org/W2574175918"],"abstract_inverted_index":{"Planar":[0],"object":[1,22,33,50,191],"tracking":[2,23,34,192,207],"is":[3,55,64,119,162,198],"an":[4],"important":[5],"research":[6],"area":[7],"of":[8,20,47,174,188],"visual":[9],"target":[10,49],"tracking.":[11],"In":[12],"order":[13],"to":[14,58,66,79,107,126,133,168],"improve":[15],"the":[16,43,48,52,59,68,72,75,80,86,92,104,109,114,122,128,136,139,149,155,159,165,170,175,179,182,186,189,201,205],"speed":[17],"and":[18,74,95,135,204],"accuracy":[19,208],"plane":[21,32],"in":[24,51,138,195],"complex":[25],"scenes,":[26],"this":[27,196],"paper":[28,197],"proposes":[29],"a":[30,123,140],"coarse-to-fine":[31],"algorithm":[35,102,147,193],"based":[36,90],"on":[37,71,91,178,209],"fully":[38],"convolutional":[39],"dense":[40,97],"network.":[41,98],"First,":[42],"estimated":[44],"bounding":[45,117],"box":[46,118,125,142],"input":[53],"image":[54,211],"calculated":[56,163],"according":[57],"DiMP50":[60],"algorithm;":[61],"then":[62,113],"SIFT":[63],"used":[65,120],"locate":[67],"key":[69,81,156],"points":[70,82],"image,":[73],"feature":[76,87,105],"descriptors":[77,106],"corresponding":[78],"are":[83,143],"extracted":[84],"from":[85,131],"map":[88],"generated":[89],"cascaded":[93],"thick":[94],"thin":[96],"The":[99],"nearest":[100],"neighbor":[101],"matches":[103],"obtain":[108,169],"paired":[110],"keypoint":[111],"set;":[112],"roughly":[115],"positioned":[116],"as":[121],"priori":[124,141],"screen":[127],"matching":[129],"keypoints":[130,137],"coarse":[132],"fine,":[134],"retained,":[144],"using":[145],"RANSAC":[146],"estimates":[148],"optimal":[150],"homography":[151,166],"matrix":[152,167],"parameters":[153],"for":[154],"points;":[157],"finally,":[158],"real":[160],"value":[161],"by":[164],"final":[171],"prediction":[172],"frame":[173],"target.":[176],"Validated":[177],"POT":[180],"dataset,":[181],"results":[183],"show":[184],"that":[185],"performance":[187],"planar":[190],"proposed":[194],"better":[199],"than":[200],"classical":[202],"algorithm,":[203],"average":[206],"all":[210],"sequences":[212],"reaches":[213],"64.76%.":[214]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}