{"id":"https://openalex.org/W4376852237","doi":"https://doi.org/10.1145/3573942.3574039","title":"Correlation Filter Based on Saliency Detection and Channel Selection for Visual Object Tracking","display_name":"Correlation Filter Based on Saliency Detection and Channel Selection for Visual Object Tracking","publication_year":2022,"publication_date":"2022-09-23","ids":{"openalex":"https://openalex.org/W4376852237","doi":"https://doi.org/10.1145/3573942.3574039"},"language":"en","primary_location":{"id":"doi:10.1145/3573942.3574039","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3573942.3574039","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 5th International Conference on Artificial Intelligence and Pattern Recognition","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/A5068927949","display_name":"Sugang Ma","orcid":"https://orcid.org/0000-0002-8588-8111"},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Sugang Ma","raw_affiliation_strings":["School of Computer Science and Technology, Xi'an University of Posts and Telecommunications, China"],"raw_orcid":"https://orcid.org/0000-0002-8588-8111","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Xi'an University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I4210136859"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024679838","display_name":"Zhixian Zhao","orcid":"https://orcid.org/0000-0002-1136-8279"},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhixian Zhao","raw_affiliation_strings":["School of Computer Science and Technology, Xi'an University of Posts and Telecommunications, China"],"raw_orcid":"https://orcid.org/0000-0002-1136-8279","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Xi'an University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I4210136859"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5116592761","display_name":"Lei Zhang","orcid":"https://orcid.org/0000-0003-1520-9360"},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Zhang","raw_affiliation_strings":["School of Computer Science and Technology, Xi'an University of Posts and Telecommunications, China"],"raw_orcid":"https://orcid.org/0000-0003-1520-9360","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Xi'an University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I4210136859"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010591797","display_name":"Lei Pu","orcid":"https://orcid.org/0000-0002-4397-2155"},"institutions":[{"id":"https://openalex.org/I2801618472","display_name":"PLA Rocket Force University of Engineering","ror":"https://ror.org/00gg5zj35","country_code":"CN","type":"education","lineage":["https://openalex.org/I2801618472"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Pu","raw_affiliation_strings":["School of Operational Support, Rocket Force Engineering University, China"],"raw_orcid":"https://orcid.org/0000-0002-4397-2155","affiliations":[{"raw_affiliation_string":"School of Operational Support, Rocket Force Engineering University, China","institution_ids":["https://openalex.org/I2801618472"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5068927949"],"corresponding_institution_ids":["https://openalex.org/I4210136859"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.17180021,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"391","last_page":"397"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9995999932289124,"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":0.9995999932289124,"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/T13567","display_name":"AI and Multimedia in Education","score":0.9958999752998352,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9714000225067139,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7447795867919922},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6940959692001343},{"id":"https://openalex.org/keywords/clutter","display_name":"Clutter","score":0.6264315247535706},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6016250848770142},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.556163489818573},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5444811582565308},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5410470366477966},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5330319404602051},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5085102319717407},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4857237935066223},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.4836212694644928},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.47940918803215027},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.4676731526851654},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.46512413024902344},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.41317883133888245},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.212800532579422},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1780681312084198},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.13503167033195496},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.10032927989959717}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7447795867919922},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6940959692001343},{"id":"https://openalex.org/C132094186","wikidata":"https://www.wikidata.org/wiki/Q641585","display_name":"Clutter","level":3,"score":0.6264315247535706},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6016250848770142},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.556163489818573},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5444811582565308},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5410470366477966},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5330319404602051},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5085102319717407},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4857237935066223},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.4836212694644928},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.47940918803215027},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.4676731526851654},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.46512413024902344},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.41317883133888245},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.212800532579422},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1780681312084198},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.13503167033195496},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.10032927989959717},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3573942.3574039","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3573942.3574039","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 5th International Conference on Artificial Intelligence and Pattern Recognition","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.5199999809265137}],"awards":[{"id":"https://openalex.org/G7321364064","display_name":null,"funder_award_id":"62072370","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1676314349","https://openalex.org/W1955741794","https://openalex.org/W2044986361","https://openalex.org/W2214352687","https://openalex.org/W2244956674","https://openalex.org/W2599547527","https://openalex.org/W2681067697","https://openalex.org/W2798842862","https://openalex.org/W2963074722","https://openalex.org/W2964069521","https://openalex.org/W3034326629","https://openalex.org/W4385415224"],"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/W4394861761","https://openalex.org/W2035264131","https://openalex.org/W1679012645","https://openalex.org/W1925461966","https://openalex.org/W2965594636"],"abstract_inverted_index":{"To":[0],"improve":[1],"the":[2,13,42,53,56,64,77,83,105,109,112,121,135,144,152],"utilization":[3],"of":[4,15,97,111,120],"convolution":[5,47],"features":[6,44,48],"by":[7,63,75],"correlation":[8,23],"filter":[9,24],"trackers":[10],"and":[11,33,45,55,82,118,126,131,175],"reduce":[12],"influence":[14],"interference":[16],"feature":[17,80,86,91],"channels":[18,92],"on":[19,30,104],"algorithm":[20,28,123,137],"performance,":[21],"a":[22,69,94,156],"visual":[25],"object":[26],"tracking":[27,160,166],"based":[29],"saliency":[31,65],"detection":[32,66],"channel":[34,70],"selection":[35,71],"is":[36,61,73],"proposed":[37,113,122,153],"in":[38,159,165],"this":[39],"paper.":[40],"Firstly,":[41],"HOG":[43],"double-layer":[46],"are":[49,124,129],"used":[50],"to":[51,88,143],"represent":[52],"target,":[54],"target":[57],"salient":[58,78],"region":[59,79,85],"mask":[60],"obtained":[62,103],"method.":[67,114],"Secondly,":[68],"mechanism":[72],"designed":[74],"using":[76],"energy":[81,87],"search":[84],"remove":[89],"redundant":[90],"containing":[93],"large":[95],"number":[96],"background":[98,173],"information.":[99],"Extensive":[100],"evaluation":[101],"results":[102],"OTB2015":[106],"benchmark":[107,136],"demonstrate":[108],"effectiveness":[110],"The":[115],"success":[116],"rate":[117],"precision":[119],"67.5%":[125],"91.3%,":[127],"which":[128],"5.4%":[130],"9.1%":[132],"higher":[133],"than":[134],"BACF,":[138],"respectively.":[139],"In":[140],"addition,":[141],"according":[142],"experimental":[145],"results,":[146],"it":[147],"can":[148],"be":[149],"seen":[150],"that":[151],"tracker":[154],"has":[155],"significant":[157],"improvement":[158],"performance":[161],"compared":[162],"with":[163,168],"competitors":[164],"scenarios":[167],"challenges":[169],"such":[170],"as":[171],"deformation,":[172],"clutter,":[174],"rotation.":[176]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}