{"id":"https://openalex.org/W2965887353","doi":"https://doi.org/10.1109/icip.2019.8803358","title":"A Ranking Based Attention Approach for Visual Tracking","display_name":"A Ranking Based Attention Approach for Visual Tracking","publication_year":2019,"publication_date":"2019-08-26","ids":{"openalex":"https://openalex.org/W2965887353","doi":"https://doi.org/10.1109/icip.2019.8803358","mag":"2965887353"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2019.8803358","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2019.8803358","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://durham-repository.worktribe.com/output/1142059","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5068882728","display_name":"Shenhui Peng","orcid":null},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Shenhui Peng","raw_affiliation_strings":["Waseda University, Kitakyushu, Japan"],"affiliations":[{"raw_affiliation_string":"Waseda University, Kitakyushu, Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066452160","display_name":"Sei\u2010ichiro Kamata","orcid":"https://orcid.org/0000-0002-1496-2417"},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Sei-ichiro Kamata","raw_affiliation_strings":["Waseda University, Kitakyushu, Japan"],"affiliations":[{"raw_affiliation_string":"Waseda University, Kitakyushu, Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045115593","display_name":"Toby P. Breckon","orcid":"https://orcid.org/0000-0003-1666-7590"},"institutions":[{"id":"https://openalex.org/I190082696","display_name":"Durham University","ror":"https://ror.org/01v29qb04","country_code":"GB","type":"education","lineage":["https://openalex.org/I190082696"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Toby P. Breckon","raw_affiliation_strings":["Durham University, Durham, UK"],"affiliations":[{"raw_affiliation_string":"Durham University, Durham, UK","institution_ids":["https://openalex.org/I190082696"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5068882728"],"corresponding_institution_ids":["https://openalex.org/I150744194"],"apc_list":null,"apc_paid":null,"fwci":0.1012,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.42836834,"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":"3073","last_page":"3077"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","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/T10331","display_name":"Video Surveillance and Tracking Methods","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/T11963","display_name":"Impact of Light on Environment and Health","score":0.9800000190734863,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9731000065803528,"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/computer-science","display_name":"Computer science","score":0.7826405763626099},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7461930513381958},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7218159437179565},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.6629895567893982},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6160851120948792},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5997408628463745},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5675513744354248},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5056858062744141},{"id":"https://openalex.org/keywords/eye-tracking","display_name":"Eye tracking","score":0.4975722134113312},{"id":"https://openalex.org/keywords/interference","display_name":"Interference (communication)","score":0.4375305771827698},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.409768283367157},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3686975836753845},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.20710930228233337}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7826405763626099},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7461930513381958},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7218159437179565},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.6629895567893982},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6160851120948792},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5997408628463745},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5675513744354248},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5056858062744141},{"id":"https://openalex.org/C56461940","wikidata":"https://www.wikidata.org/wiki/Q970687","display_name":"Eye tracking","level":2,"score":0.4975722134113312},{"id":"https://openalex.org/C32022120","wikidata":"https://www.wikidata.org/wiki/Q797225","display_name":"Interference (communication)","level":3,"score":0.4375305771827698},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.409768283367157},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3686975836753845},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.20710930228233337},{"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},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","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/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/icip.2019.8803358","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2019.8803358","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},{"id":"pmh:oai:dro.dur.ac.uk.OAI2:28331","is_oa":false,"landing_page_url":"http://dro.dur.ac.uk/28331/","pdf_url":null,"source":{"id":"https://openalex.org/S4377196258","display_name":"Durham Research Online (Durham University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I190082696","host_organization_name":"Durham University","host_organization_lineage":["https://openalex.org/I190082696"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"(2019). 2019 IEEE International Conference on Image Processing (ICIP) ; proceedings. Piscataway, NJ: IEEE, pp. 3073-3077","raw_type":"Book chapter"},{"id":"pmh:oai:durham-repository.worktribe.com:1142059","is_oa":true,"landing_page_url":"https://durham-repository.worktribe.com/output/1142059","pdf_url":null,"source":{"id":"https://openalex.org/S4306400188","display_name":"Durham Research Online (Durham University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I190082696","host_organization_name":"Durham University","host_organization_lineage":["https://openalex.org/I190082696"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"acceptedVersion"}],"best_oa_location":{"id":"pmh:oai:durham-repository.worktribe.com:1142059","is_oa":true,"landing_page_url":"https://durham-repository.worktribe.com/output/1142059","pdf_url":null,"source":{"id":"https://openalex.org/S4306400188","display_name":"Durham Research Online (Durham University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I190082696","host_organization_name":"Durham University","host_organization_lineage":["https://openalex.org/I190082696"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"acceptedVersion"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1849277567","https://openalex.org/W1915785815","https://openalex.org/W1955741794","https://openalex.org/W1964846093","https://openalex.org/W2089961441","https://openalex.org/W2151103935","https://openalex.org/W2154889144","https://openalex.org/W2158592639","https://openalex.org/W2161969291","https://openalex.org/W2244956674","https://openalex.org/W2470394683","https://openalex.org/W2518876086","https://openalex.org/W2740685955","https://openalex.org/W2799058067","https://openalex.org/W2894961023","https://openalex.org/W2962835968","https://openalex.org/W2963272600","https://openalex.org/W2963499285","https://openalex.org/W2963873961","https://openalex.org/W2964111344","https://openalex.org/W3102624093","https://openalex.org/W6637373629","https://openalex.org/W6639204139","https://openalex.org/W6720898849"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W4321353415","https://openalex.org/W2745001401","https://openalex.org/W2130974462","https://openalex.org/W2028665553","https://openalex.org/W2086519370","https://openalex.org/W972276598","https://openalex.org/W4246352526","https://openalex.org/W2121910908","https://openalex.org/W2964954556"],"abstract_inverted_index":{"Correlation":[0],"filters":[1],"(CF)":[2],"combined":[3],"with":[4,59],"pre-trained":[5],"convolutional":[6,74,101],"neural":[7],"network":[8,79],"(CNN)":[9],"feature":[10],"extractors":[11],"have":[12],"shown":[13],"an":[14],"admirable":[15],"accuracy":[16],"and":[17,34,69,95],"speed":[18],"in":[19],"visual":[20],"object":[21],"tracking.":[22],"However,":[23],"existing":[24],"CNN-CF":[25],"based":[26,49],"methods":[27],"still":[28],"suffer":[29],"from":[30],"the":[31,93,107],"background":[32,57],"interference":[33,58],"boundary":[35],"effects,":[36],"even":[37],"when":[38],"a":[39,47,73,98],"cosine":[40],"window":[41],"is":[42,81,103],"introduced.":[43],"This":[44,63],"paper":[45],"proposes":[46],"ranking":[48,64],"or":[50],"guided":[51],"attention":[52],"approach":[53],"which":[54,87],"can":[55],"reduce":[56],"only":[60],"forward":[61],"propagation.":[62],"stores":[65],"several":[66],"convolution":[67],"kernels":[68],"scores":[70],"them.":[71],"Subsequently,":[72],"Long":[75],"Short":[76],"Time":[77],"Memory":[78],"(ConvLSTM)":[80],"used":[82],"to":[83,92,105],"update":[84],"this":[85],"ranking,":[86],"makes":[88],"it":[89],"more":[90],"robust":[91],"variation":[94],"occlusion.":[96],"Moreover,":[97],"part-based":[99],"multi-channel":[100],"tracker":[102],"proposed":[104],"obtain":[106],"final":[108],"response":[109],"map.":[110],"Our":[111],"extensive":[112],"experiments":[113],"on":[114],"established":[115],"benchmark":[116],"datasets":[117],"show":[118],"comparable":[119],"performance":[120],"against":[121],"contemporary":[122],"tracking":[123],"approaches.":[124]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}