{"id":"https://openalex.org/W2411544765","doi":"https://doi.org/10.1145/2911996.2912008","title":"Foreground Object Sensing for Saliency Detection","display_name":"Foreground Object Sensing for Saliency Detection","publication_year":2016,"publication_date":"2016-06-06","ids":{"openalex":"https://openalex.org/W2411544765","doi":"https://doi.org/10.1145/2911996.2912008","mag":"2411544765"},"language":"en","primary_location":{"id":"doi:10.1145/2911996.2912008","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2911996.2912008","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2016 ACM on International Conference on Multimedia Retrieval","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/A5101540187","display_name":"Hengliang Zhu","orcid":"https://orcid.org/0000-0002-5034-1044"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hengliang Zhu","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102765877","display_name":"Bin Sheng","orcid":"https://orcid.org/0000-0001-8510-2556"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Sheng","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100450522","display_name":"Xiao Lin","orcid":"https://orcid.org/0000-0002-8805-7129"},"institutions":[{"id":"https://openalex.org/I148128674","display_name":"University of Shanghai for Science and Technology","ror":"https://ror.org/00ay9v204","country_code":"CN","type":"education","lineage":["https://openalex.org/I148128674"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao Lin","raw_affiliation_strings":["University of Shanghai for science and technology, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Shanghai for science and technology, Shanghai, China","institution_ids":["https://openalex.org/I148128674"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043706524","display_name":"Yangyang Hao","orcid":"https://orcid.org/0009-0009-4374-1566"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yangyang Hao","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084218062","display_name":"Lizhuang Ma","orcid":"https://orcid.org/0000-0003-1653-4341"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lizhuang Ma","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.0141,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.82885729,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"111","last_page":"118"},"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/T10971","display_name":"Olfactory and Sensory Function Studies","score":0.9907000064849854,"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"}},{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9905999898910522,"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/convex-hull","display_name":"Convex hull","score":0.8558343648910522},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6760849952697754},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6715418696403503},{"id":"https://openalex.org/keywords/boundary","display_name":"Boundary (topology)","score":0.6335371136665344},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.606048583984375},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5862514972686768},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5755733251571655},{"id":"https://openalex.org/keywords/saliency-map","display_name":"Saliency map","score":0.5496115684509277},{"id":"https://openalex.org/keywords/regular-polygon","display_name":"Regular polygon","score":0.47941964864730835},{"id":"https://openalex.org/keywords/convex-combination","display_name":"Convex combination","score":0.4572455883026123},{"id":"https://openalex.org/keywords/orthogonal-convex-hull","display_name":"Orthogonal convex hull","score":0.4508896470069885},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44344860315322876},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4358952045440674},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.42075347900390625},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3327651023864746},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3212568163871765},{"id":"https://openalex.org/keywords/convex-optimization","display_name":"Convex optimization","score":0.2261776626110077},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.08431923389434814},{"id":"https://openalex.org/keywords/convex-body","display_name":"Convex body","score":0.08374440670013428}],"concepts":[{"id":"https://openalex.org/C206194317","wikidata":"https://www.wikidata.org/wiki/Q1138624","display_name":"Convex hull","level":3,"score":0.8558343648910522},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6760849952697754},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6715418696403503},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.6335371136665344},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.606048583984375},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5862514972686768},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5755733251571655},{"id":"https://openalex.org/C2779679900","wikidata":"https://www.wikidata.org/wiki/Q25304431","display_name":"Saliency map","level":3,"score":0.5496115684509277},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.47941964864730835},{"id":"https://openalex.org/C111110010","wikidata":"https://www.wikidata.org/wiki/Q2627315","display_name":"Convex combination","level":4,"score":0.4572455883026123},{"id":"https://openalex.org/C64051489","wikidata":"https://www.wikidata.org/wiki/Q7104528","display_name":"Orthogonal convex hull","level":5,"score":0.4508896470069885},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44344860315322876},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4358952045440674},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.42075347900390625},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3327651023864746},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3212568163871765},{"id":"https://openalex.org/C157972887","wikidata":"https://www.wikidata.org/wiki/Q463359","display_name":"Convex optimization","level":3,"score":0.2261776626110077},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.08431923389434814},{"id":"https://openalex.org/C134912446","wikidata":"https://www.wikidata.org/wiki/Q5166516","display_name":"Convex body","level":4,"score":0.08374440670013428},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2911996.2912008","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2911996.2912008","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2016 ACM on International Conference on Multimedia Retrieval","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.6600000262260437}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W21025885","https://openalex.org/W1497599070","https://openalex.org/W1510835000","https://openalex.org/W1872412942","https://openalex.org/W1897243830","https://openalex.org/W1918837316","https://openalex.org/W1966822461","https://openalex.org/W1981228217","https://openalex.org/W1982075130","https://openalex.org/W1996326832","https://openalex.org/W2002574940","https://openalex.org/W2002781701","https://openalex.org/W2003294379","https://openalex.org/W2015196405","https://openalex.org/W2020523103","https://openalex.org/W2032007016","https://openalex.org/W2036576620","https://openalex.org/W2037954058","https://openalex.org/W2039313011","https://openalex.org/W2040253108","https://openalex.org/W2047670868","https://openalex.org/W2055289854","https://openalex.org/W2078132377","https://openalex.org/W2086791339","https://openalex.org/W2087100776","https://openalex.org/W2093353037","https://openalex.org/W2097878628","https://openalex.org/W2098702446","https://openalex.org/W2100470808","https://openalex.org/W2107363596","https://openalex.org/W2118246710","https://openalex.org/W2120504013","https://openalex.org/W2122076510","https://openalex.org/W2124351162","https://openalex.org/W2128272608","https://openalex.org/W2128340050","https://openalex.org/W2130184867","https://openalex.org/W2130502991","https://openalex.org/W2130637418","https://openalex.org/W2133589685","https://openalex.org/W2135957164","https://openalex.org/W2140654078","https://openalex.org/W2146103513","https://openalex.org/W2156777442","https://openalex.org/W2159772167","https://openalex.org/W2161185676","https://openalex.org/W2567978322","https://openalex.org/W2768066693","https://openalex.org/W3098389804","https://openalex.org/W4236965008","https://openalex.org/W6639624585","https://openalex.org/W6680437723","https://openalex.org/W6784647857"],"related_works":["https://openalex.org/W2300145982","https://openalex.org/W2580512045","https://openalex.org/W2365830408","https://openalex.org/W1569666406","https://openalex.org/W2375652826","https://openalex.org/W2100104291","https://openalex.org/W2048874717","https://openalex.org/W1507382935","https://openalex.org/W2363904277","https://openalex.org/W1500255470"],"abstract_inverted_index":{"Many":[0],"state-of-the-art":[1],"saliency":[2,61,123],"detection":[3],"algorithms":[4,12,138],"rely":[5],"on":[6,92,141],"the":[7,15,44,49,60,71,95,103,107,113,122,131,144],"boundary":[8],"prior,":[9],"but":[10],"these":[11],"simply":[13],"suppose":[14],"boundaries":[16],"around":[17],"an":[18],"image":[19],"as":[20],"background":[21],"regions.":[22],"Here":[23],"we":[24,58],"propose":[25],"a":[26,36,82,88],"fast":[27],"and":[28,69,76,112,139,153],"effective":[29],"algorithm":[30,146],"for":[31],"salient":[32],"object":[33,46],"detection.":[34],"First,":[35],"novel":[37],"method":[38],"is":[39,99,126],"proposed":[40,100],"to":[41,94,101,120,129],"approximately":[42],"locate":[43],"foreground":[45],"by":[47],"using":[48],"convex":[50,83,96,108,114],"hull":[51,84,97,109,115],"from":[52],"Harris":[53],"corner.":[54],"On":[55],"this":[56],"basis,":[57],"divide":[59],"values":[62],"of":[63,151],"different":[64],"regions":[65],"into":[66,81],"two":[67],"parts":[68],"generate":[70],"corresponding":[72],"cue":[73],"maps":[74],"(foreground":[75],"background),":[77],"which":[78,125],"are":[79,118],"combined":[80,119],"prior":[85,90,110],"map.":[86],"Then":[87],"new":[89],"based":[91],"distance":[93],"center":[98,104],"replace":[102],"prior.":[105],"Finally,":[106],"map":[111,117],"center-biased":[116],"be":[121],"map,":[124],"then":[127],"optimized":[128],"get":[130],"final":[132],"result.":[133],"Compared":[134],"with":[135],"eighteen":[136],"existing":[137],"tested":[140],"several":[142],"datasets,":[143],"present":[145],"performs":[147],"well":[148],"in":[149],"terms":[150],"precision":[152],"recall.":[154]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}