{"id":"https://openalex.org/W2301941309","doi":"https://doi.org/10.1109/lsp.2016.2544781","title":"Saliency Detection With Spaces of Background-Based Distribution","display_name":"Saliency Detection With Spaces of Background-Based Distribution","publication_year":2016,"publication_date":"2016-03-22","ids":{"openalex":"https://openalex.org/W2301941309","doi":"https://doi.org/10.1109/lsp.2016.2544781","mag":"2301941309"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2016.2544781","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2016.2544781","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1603.05335","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5035766567","display_name":"Tong Zhao","orcid":"https://orcid.org/0000-0001-7660-1732"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Tong Zhao","raw_affiliation_strings":["School of Information Science and Engineering, Xiamen University, Xiamen, China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100412926","display_name":"Lin Li","orcid":"https://orcid.org/0000-0003-0426-6546"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lin Li","raw_affiliation_strings":["School of Information Science and Engineering, Xiamen University, Xiamen, China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052820597","display_name":"Xinghao Ding","orcid":"https://orcid.org/0000-0003-2288-5287"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinghao Ding","raw_affiliation_strings":["School of Information Science and Engineering, Xiamen University, Xiamen, China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100772804","display_name":"Yue Huang","orcid":"https://orcid.org/0000-0002-3913-9400"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yue Huang","raw_affiliation_strings":["School of Information Science and Engineering, Xiamen University, Xiamen, China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005221942","display_name":"Delu Zeng","orcid":"https://orcid.org/0000-0001-7322-1873"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Delu Zeng","raw_affiliation_strings":["School of Information Science and Engineering, Xiamen University, Xiamen, China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I191208505"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5035766567"],"corresponding_institution_ids":["https://openalex.org/I191208505"],"apc_list":null,"apc_paid":null,"fwci":2.5419,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":{"value":0.92933183,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"23","issue":"5","first_page":"683","last_page":"687"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","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/T11605","display_name":"Visual Attention and Saliency Detection","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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9872999787330627,"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/T10971","display_name":"Olfactory and Sensory Function Studies","score":0.9815999865531921,"subfield":{"id":"https://openalex.org/subfields/2809","display_name":"Sensory Systems"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/mahalanobis-distance","display_name":"Mahalanobis distance","score":0.8797773122787476},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7222022414207458},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6430648565292358},{"id":"https://openalex.org/keywords/geodesic","display_name":"Geodesic","score":0.6287351846694946},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5776982307434082},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.5574766397476196},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5471190810203552},{"id":"https://openalex.org/keywords/posterior-probability","display_name":"Posterior probability","score":0.530362606048584},{"id":"https://openalex.org/keywords/saliency-map","display_name":"Saliency map","score":0.505791187286377},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.49088555574417114},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4762958586215973},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4665954113006592},{"id":"https://openalex.org/keywords/probability-distribution","display_name":"Probability distribution","score":0.4351796507835388},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.4297177493572235},{"id":"https://openalex.org/keywords/foreground-detection","display_name":"Foreground detection","score":0.4177641272544861},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.35566824674606323},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.3382214307785034},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1284545361995697},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.09948047995567322}],"concepts":[{"id":"https://openalex.org/C1921717","wikidata":"https://www.wikidata.org/wiki/Q1334846","display_name":"Mahalanobis distance","level":2,"score":0.8797773122787476},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7222022414207458},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6430648565292358},{"id":"https://openalex.org/C165818556","wikidata":"https://www.wikidata.org/wiki/Q213488","display_name":"Geodesic","level":2,"score":0.6287351846694946},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5776982307434082},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5574766397476196},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5471190810203552},{"id":"https://openalex.org/C57830394","wikidata":"https://www.wikidata.org/wiki/Q278079","display_name":"Posterior probability","level":3,"score":0.530362606048584},{"id":"https://openalex.org/C2779679900","wikidata":"https://www.wikidata.org/wiki/Q25304431","display_name":"Saliency map","level":3,"score":0.505791187286377},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.49088555574417114},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4762958586215973},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4665954113006592},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.4351796507835388},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.4297177493572235},{"id":"https://openalex.org/C2779769447","wikidata":"https://www.wikidata.org/wiki/Q3813641","display_name":"Foreground detection","level":4,"score":0.4177641272544861},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.35566824674606323},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.3382214307785034},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1284545361995697},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.09948047995567322},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/lsp.2016.2544781","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2016.2544781","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1603.05335","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1603.05335","pdf_url":"https://arxiv.org/pdf/1603.05335","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1603.05335","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1603.05335","pdf_url":"https://arxiv.org/pdf/1603.05335","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7799999713897705}],"awards":[{"id":"https://openalex.org/G1060893916","display_name":null,"funder_award_id":"20720150093","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G2680065437","display_name":null,"funder_award_id":"61103121","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3527375350","display_name":null,"funder_award_id":"81301278","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4197034150","display_name":null,"funder_award_id":"20120121120043","funder_id":"https://openalex.org/F4320336024","funder_display_name":"Specialized Research Fund for the Doctoral Program of Higher Education of China"},{"id":"https://openalex.org/G7282001549","display_name":null,"funder_award_id":"61571005","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7515390380","display_name":null,"funder_award_id":"20720150169","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G764035562","display_name":null,"funder_award_id":"61571382","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8507328295","display_name":null,"funder_award_id":"61172179","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8797443548","display_name":null,"funder_award_id":"20720160075","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null},{"id":"https://openalex.org/F4320336024","display_name":"Specialized Research Fund for the Doctoral Program of Higher Education of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W21025885","https://openalex.org/W892735016","https://openalex.org/W1538842650","https://openalex.org/W1588168368","https://openalex.org/W1593956231","https://openalex.org/W1719407190","https://openalex.org/W1772076007","https://openalex.org/W1938929646","https://openalex.org/W1944582599","https://openalex.org/W1966822461","https://openalex.org/W1982075130","https://openalex.org/W1996326832","https://openalex.org/W2002781701","https://openalex.org/W2023240564","https://openalex.org/W2028327943","https://openalex.org/W2036973297","https://openalex.org/W2037954058","https://openalex.org/W2039313011","https://openalex.org/W2045775567","https://openalex.org/W2047670868","https://openalex.org/W2055180303","https://openalex.org/W2080142539","https://openalex.org/W2105454024","https://openalex.org/W2122076510","https://openalex.org/W2128340050","https://openalex.org/W2152233525","https://openalex.org/W2161185676","https://openalex.org/W3098389804","https://openalex.org/W3103604207","https://openalex.org/W3104979525","https://openalex.org/W4239147634","https://openalex.org/W6640464587","https://openalex.org/W6670748880","https://openalex.org/W6784647857"],"related_works":["https://openalex.org/W2766247743","https://openalex.org/W2513302492","https://openalex.org/W2990096089","https://openalex.org/W2947626973","https://openalex.org/W1990509243","https://openalex.org/W2963941678","https://openalex.org/W2186741113","https://openalex.org/W2016334866","https://openalex.org/W2909025823","https://openalex.org/W2091287383"],"abstract_inverted_index":{"In":[0],"this":[1],"letter,":[2],"an":[3],"effective":[4,157],"image":[5,69],"saliency":[6,66,79,115,131],"detection":[7],"method":[8,155],"is":[9,38,60,81,94,117,133,156],"proposed":[10,154],"by":[11,83,96,135],"constructing":[12],"some":[13],"novel":[14],"spaces":[15,43],"to":[16,40,48,62],"model":[17,49],"the":[18,22,25,30,34,50,65,73,85,97,101,106,113,121,129,138,153,160],"background":[19,104],"and":[20,103],"redefine":[21],"distance":[23,89],"of":[24,44,67,92],"salient":[26],"patches":[27,102],"away":[28,71],"from":[29,72],"background.":[31,74],"Concretely,":[32],"given":[33],"backgroundness":[35],"prior,":[36],"eigendecomposition":[37],"utilized":[39],"create":[41],"four":[42,86],"background-based":[45],"distribution":[46],"(SBD)":[47],"background,":[51],"in":[52,105],"which":[53,93],"a":[54,77],"more":[55,111],"appropriate":[56],"metric":[57],"(Mahalanobis":[58],"distance)":[59],"quoted":[61],"delicately":[63],"measure":[64],"every":[68],"patch":[70],"After":[75],"that,":[76],"coarse":[78,114],"map":[80,116,124,132,141],"obtained":[82],"integrating":[84],"adjusted":[87],"Mahalanobis":[88],"maps,":[90],"each":[91],"formed":[95],"distances":[98],"between":[99],"all":[100],"corresponding":[107],"SBD.":[108],"To":[109],"be":[110],"discriminative,":[112],"further":[118],"enhanced":[119],"into":[120],"posterior":[122,139],"probability":[123,140],"within":[125],"Bayesian":[126],"perspective.":[127],"Finally,":[128],"final":[130],"generated":[134],"properly":[136],"refining":[137],"with":[142,159],"geodesic":[143],"distance.":[144],"Experimental":[145],"results":[146],"on":[147],"two":[148],"usual":[149],"datasets":[150],"show":[151],"that":[152],"compared":[158],"state-of-the-art":[161],"algorithms.":[162]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":8},{"year":2016,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}