{"id":"https://openalex.org/W4399658657","doi":"https://doi.org/10.1145/3641584.3641668","title":"Object Tracking Algorithm based on Transformer with Temporal Contexts","display_name":"Object Tracking Algorithm based on Transformer with Temporal Contexts","publication_year":2023,"publication_date":"2023-09-22","ids":{"openalex":"https://openalex.org/W4399658657","doi":"https://doi.org/10.1145/3641584.3641668"},"language":"en","primary_location":{"id":"doi:10.1145/3641584.3641668","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3641584.3641668","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 6th International Conference on Artificial Intelligence and Pattern Recognition (AIPR)","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/A5072893138","display_name":"Na Li","orcid":"https://orcid.org/0000-0002-2547-3993"},"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":"Na Li","raw_affiliation_strings":["Xi'an University of Posts and Telecommunications, China"],"raw_orcid":"https://orcid.org/0000-0002-2547-3993","affiliations":[{"raw_affiliation_string":"Xi'an University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I4210136859"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072580832","display_name":"Wenhan Jiang","orcid":"https://orcid.org/0000-0002-9762-1596"},"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":"Wenhan Jiang","raw_affiliation_strings":["Xi'an University of Posts and Telecommunications, China"],"raw_orcid":"https://orcid.org/0000-0003-3481-0530","affiliations":[{"raw_affiliation_string":"Xi'an University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I4210136859"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000287326","display_name":"Mengqiao Liu","orcid":"https://orcid.org/0009-0007-5983-6741"},"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":"Mengqiao Liu","raw_affiliation_strings":["Xi'an University of Posts and Telecommunications, China"],"raw_orcid":"https://orcid.org/0009-0007-5983-6741","affiliations":[{"raw_affiliation_string":"Xi'an University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I4210136859"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5099124675","display_name":"Wanyv Xin","orcid":"https://orcid.org/0009-0002-1611-4195"},"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":"Wanyv Xin","raw_affiliation_strings":["Xi'an University of Posts and Telecommunications, China"],"raw_orcid":"https://orcid.org/0009-0002-1611-4195","affiliations":[{"raw_affiliation_string":"Xi'an University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I4210136859"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5072893138"],"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":0.22262536,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"564","last_page":"570"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9993000030517578,"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":0.9993000030517578,"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/T12597","display_name":"Fire Detection and Safety Systems","score":0.9718000292778015,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9606000185012817,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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":0.7002936601638794},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5023829936981201},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5005805492401123},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.45707425475120544},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.44772085547447205},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.41927802562713623},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.37444037199020386},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.32888340950012207},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09984788298606873},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.0616777241230011}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7002936601638794},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5023829936981201},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5005805492401123},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.45707425475120544},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.44772085547447205},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.41927802562713623},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.37444037199020386},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.32888340950012207},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09984788298606873},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0616777241230011},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3641584.3641668","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3641584.3641668","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 6th International Conference on Artificial Intelligence and Pattern Recognition (AIPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W2343187456","https://openalex.org/W2520477759","https://openalex.org/W2963936229","https://openalex.org/W2966633638","https://openalex.org/W3017243358","https://openalex.org/W3042016044","https://openalex.org/W3146450052","https://openalex.org/W3172446114","https://openalex.org/W3190695173","https://openalex.org/W4225726864","https://openalex.org/W4255496528","https://openalex.org/W4300789046","https://openalex.org/W4317935402"],"related_works":["https://openalex.org/W4389065903","https://openalex.org/W2158788032","https://openalex.org/W2385949326","https://openalex.org/W1966005655","https://openalex.org/W3135795035","https://openalex.org/W2789220062","https://openalex.org/W2811496562","https://openalex.org/W2094665863","https://openalex.org/W2071984725","https://openalex.org/W2185534064"],"abstract_inverted_index":{"Most":[0],"existing":[1],"trackers":[2],"rely":[3],"solely":[4],"on":[5,47,100,137],"current":[6],"frame":[7],"information":[8,70],"for":[9],"object":[10,43,130],"tracking.":[11,182],"As":[12],"a":[13,42,56,91],"result,":[14],"phenomena":[15],"such":[16,27,169],"as":[17,28,170],"drifting":[18],"or":[19],"tracking":[20,44],"failures":[21],"occur":[22],"when":[23],"complex":[24,167],"situations":[25],"arise,":[26],"out-of-view,":[29,171],"fast":[30,172],"motion":[31,33,175],"and":[32,86,121,140,174],"blur.":[34],"To":[35],"address":[36],"these":[37],"issues,":[38],"this":[39,53],"paper":[40,54],"proposes":[41],"algorithm":[45,151,164],"based":[46],"Transformer":[48],"with":[49],"temporal":[50,57],"contexts.":[51],"Firstly,":[52],"presents":[55],"adaptive":[58],"network,":[59],"where":[60],"dynamically":[61],"calibrated":[62],"weights":[63,77],"are":[64,78,88,135],"utilized":[65],"to":[66,145],"fuse":[67],"the":[68,75,81,96,101,127,138,153,162,179],"feature":[69,84,97],"from":[71],"adjacent":[72],"frames.":[73],"Specifically,":[74],"calibration":[76],"extracted":[79],"using":[80,90],"bottleneck.":[82],"Subsequently,":[83],"enhancement":[85],"fusion":[87],"performed":[89],"transformer":[92],"module,":[93],"which":[94],"enhances":[95],"representation.":[98],"Lastly,":[99],"basis":[102],"of":[103,129,181],"intersection-over-union":[104],"loss,":[105],"an":[106],"improved":[107],"localization":[108],"loss":[109],"function":[110],"was":[111],"designed":[112],"by":[113],"incorporating":[114],"two":[115],"additional":[116],"factors,":[117],"center":[118],"point":[119],"distance":[120],"aspect":[122],"ratio,":[123],"thereby":[124,177],"further":[125],"enhancing":[126],"accuracy":[128],"scale":[131],"estimation.":[132],"Extensive":[133],"experiments":[134],"conducted":[136],"UAV123":[139],"OTB100":[141],"datasets.":[142],"And":[143],"compared":[144],"four":[146],"other":[147],"algorithms,":[148],"our":[149],"proposed":[150,163],"achieved":[152],"overall":[154],"best":[155],"performance.":[156],"The":[157],"experimental":[158],"results":[159],"show":[160],"that":[161],"effectively":[165],"handles":[166],"factors":[168],"motion,":[173],"blur,":[176],"improving":[178],"quality":[180]},"counts_by_year":[],"updated_date":"2025-12-23T23:11:35.936235","created_date":"2025-10-10T00:00:00"}
