{"id":"https:\/\/openalex.org\/W3117745303","doi":"https:\/\/doi.org\/10.1109\/vcip49819.2020.9301776","title":"A Marked Point Process Model For Visual Perceptual Groups Extraction","display_name":"A Marked Point Process Model For Visual Perceptual Groups Extraction","publication_year":2020,"publication_date":"2020-12-01","ids":{"openalex":"https:\/\/openalex.org\/W3117745303","doi":"https:\/\/doi.org\/10.1109\/vcip49819.2020.9301776","mag":"3117745303"},"language":"en","primary_location":{"id":"doi:10.1109\/vcip49819.2020.9301776","is_oa":false,"landing_page_url":"https:\/\/doi.org\/10.1109\/vcip49819.2020.9301776","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Visual Communications and Image Processing (VCIP)","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\/A5041894821","display_name":"Amal Mbarki","orcid":"https:\/\/orcid.org\/0000-0001-5170-150X"},"institutions":[{"id":"https:\/\/openalex.org\/I63596082","display_name":"Tunis El Manar University","ror":"https:\/\/ror.org\/029cgt552","country_code":"TN","type":"education","lineage":["https:\/\/openalex.org\/I63596082"]},{"id":"https:\/\/openalex.org\/I108714496","display_name":"Tunis University","ror":"https:\/\/ror.org\/02q1spa57","country_code":"TN","type":"education","lineage":["https:\/\/openalex.org\/I108714496"]}],"countries":["TN"],"is_corresponding":true,"raw_author_name":"Amal Mbarki","raw_affiliation_strings":["Faculty of Sciences of Tunis, University of Tunis EL MANAR, Tunis, Tunisia"],"affiliations":[{"raw_affiliation_string":"Faculty of Sciences of Tunis, University of Tunis EL MANAR, Tunis, Tunisia","institution_ids":["https:\/\/openalex.org\/I63596082","https:\/\/openalex.org\/I108714496"]}]},{"author_position":"last","author":{"id":"https:\/\/openalex.org\/A5034274597","display_name":"Mohamed Naouai","orcid":null},"institutions":[{"id":"https:\/\/openalex.org\/I108714496","display_name":"Tunis University","ror":"https:\/\/ror.org\/02q1spa57","country_code":"TN","type":"education","lineage":["https:\/\/openalex.org\/I108714496"]},{"id":"https:\/\/openalex.org\/I63596082","display_name":"Tunis El Manar University","ror":"https:\/\/ror.org\/029cgt552","country_code":"TN","type":"education","lineage":["https:\/\/openalex.org\/I63596082"]}],"countries":["TN"],"is_corresponding":false,"raw_author_name":"Mohamed Naouai","raw_affiliation_strings":["Faculty of Sciences of Tunis, University of Tunis EL MANAR, Tunis, Tunisia"],"affiliations":[{"raw_affiliation_string":"Faculty of Sciences of Tunis, University of Tunis EL MANAR, Tunis, Tunisia","institution_ids":["https:\/\/openalex.org\/I63596082","https:\/\/openalex.org\/I108714496"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https:\/\/openalex.org\/A5041894821"],"corresponding_institution_ids":["https:\/\/openalex.org\/I108714496","https:\/\/openalex.org\/I63596082"],"apc_list":null,"apc_paid":null,"fwci":1.1556,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.78758967,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"122","issue":null,"first_page":"511","last_page":"514"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https:\/\/openalex.org\/T12417","display_name":"Morphological variations and asymmetry","score":0.9950000047683716,"subfield":{"id":"https:\/\/openalex.org\/subfields\/2608","display_name":"Geometry and Topology"},"field":{"id":"https:\/\/openalex.org\/fields\/26","display_name":"Mathematics"},"domain":{"id":"https:\/\/openalex.org\/domains\/3","display_name":"Physical Sciences"}},"topics":[{"id":"https:\/\/openalex.org\/T12417","display_name":"Morphological variations and asymmetry","score":0.9950000047683716,"subfield":{"id":"https:\/\/openalex.org\/subfields\/2608","display_name":"Geometry and Topology"},"field":{"id":"https:\/\/openalex.org\/fields\/26","display_name":"Mathematics"},"domain":{"id":"https:\/\/openalex.org\/domains\/3","display_name":"Physical Sciences"}},{"id":"https:\/\/openalex.org\/T10052","display_name":"Medical Image Segmentation Techniques","score":0.994700014591217,"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\/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9912999868392944,"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":0.6801167726516724},{"id":"https:\/\/openalex.org\/keywords\/process","display_name":"Process (computing)","score":0.6291019320487976},{"id":"https:\/\/openalex.org\/keywords\/perception","display_name":"Perception","score":0.5622175931930542},{"id":"https:\/\/openalex.org\/keywords\/extraction","display_name":"Extraction (chemistry)","score":0.5569486618041992},{"id":"https:\/\/openalex.org\/keywords\/point","display_name":"Point (geometry)","score":0.5329003930091858},{"id":"https:\/\/openalex.org\/keywords\/artificial-intelligence","display_name":"Artificial intelligence","score":0.4949726462364197},{"id":"https:\/\/openalex.org\/keywords\/point-process","display_name":"Point process","score":0.42768147587776184},{"id":"https:\/\/openalex.org\/keywords\/computer-vision","display_name":"Computer vision","score":0.3894188702106476},{"id":"https:\/\/openalex.org\/keywords\/mathematics","display_name":"Mathematics","score":0.1862247884273529},{"id":"https:\/\/openalex.org\/keywords\/psychology","display_name":"Psychology","score":0.15635302662849426},{"id":"https:\/\/openalex.org\/keywords\/statistics","display_name":"Statistics","score":0.14978709816932678},{"id":"https:\/\/openalex.org\/keywords\/programming-language","display_name":"Programming language","score":0.08609634637832642},{"id":"https:\/\/openalex.org\/keywords\/geometry","display_name":"Geometry","score":0.07705065608024597}],"concepts":[{"id":"https:\/\/openalex.org\/C41008148","wikidata":"https:\/\/www.wikidata.org\/wiki\/Q21198","display_name":"Computer science","level":0,"score":0.6801167726516724},{"id":"https:\/\/openalex.org\/C98045186","wikidata":"https:\/\/www.wikidata.org\/wiki\/Q205663","display_name":"Process (computing)","level":2,"score":0.6291019320487976},{"id":"https:\/\/openalex.org\/C26760741","wikidata":"https:\/\/www.wikidata.org\/wiki\/Q160402","display_name":"Perception","level":2,"score":0.5622175931930542},{"id":"https:\/\/openalex.org\/C4725764","wikidata":"https:\/\/www.wikidata.org\/wiki\/Q844704","display_name":"Extraction (chemistry)","level":2,"score":0.5569486618041992},{"id":"https:\/\/openalex.org\/C28719098","wikidata":"https:\/\/www.wikidata.org\/wiki\/Q44946","display_name":"Point (geometry)","level":2,"score":0.5329003930091858},{"id":"https:\/\/openalex.org\/C154945302","wikidata":"https:\/\/www.wikidata.org\/wiki\/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4949726462364197},{"id":"https:\/\/openalex.org\/C88871306","wikidata":"https:\/\/www.wikidata.org\/wiki\/Q7208287","display_name":"Point process","level":2,"score":0.42768147587776184},{"id":"https:\/\/openalex.org\/C31972630","wikidata":"https:\/\/www.wikidata.org\/wiki\/Q844240","display_name":"Computer vision","level":1,"score":0.3894188702106476},{"id":"https:\/\/openalex.org\/C33923547","wikidata":"https:\/\/www.wikidata.org\/wiki\/Q395","display_name":"Mathematics","level":0,"score":0.1862247884273529},{"id":"https:\/\/openalex.org\/C15744967","wikidata":"https:\/\/www.wikidata.org\/wiki\/Q9418","display_name":"Psychology","level":0,"score":0.15635302662849426},{"id":"https:\/\/openalex.org\/C105795698","wikidata":"https:\/\/www.wikidata.org\/wiki\/Q12483","display_name":"Statistics","level":1,"score":0.14978709816932678},{"id":"https:\/\/openalex.org\/C199360897","wikidata":"https:\/\/www.wikidata.org\/wiki\/Q9143","display_name":"Programming language","level":1,"score":0.08609634637832642},{"id":"https:\/\/openalex.org\/C2524010","wikidata":"https:\/\/www.wikidata.org\/wiki\/Q8087","display_name":"Geometry","level":1,"score":0.07705065608024597},{"id":"https:\/\/openalex.org\/C169760540","wikidata":"https:\/\/www.wikidata.org\/wiki\/Q207011","display_name":"Neuroscience","level":1,"score":0},{"id":"https:\/\/openalex.org\/C43617362","wikidata":"https:\/\/www.wikidata.org\/wiki\/Q170050","display_name":"Chromatography","level":1,"score":0},{"id":"https:\/\/openalex.org\/C185592680","wikidata":"https:\/\/www.wikidata.org\/wiki\/Q2329","display_name":"Chemistry","level":0,"score":0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109\/vcip49819.2020.9301776","is_oa":false,"landing_page_url":"https:\/\/doi.org\/10.1109\/vcip49819.2020.9301776","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Visual Communications and Image Processing (VCIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8100000023841858,"display_name":"Peace, Justice and strong institutions","id":"https:\/\/metadata.un.org\/sdg\/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https:\/\/openalex.org\/W1860237464","https:\/\/openalex.org\/W2036591396","https:\/\/openalex.org\/W2037947871","https:\/\/openalex.org\/W2106706098","https:\/\/openalex.org\/W2198731777","https:\/\/openalex.org\/W2211564018","https:\/\/openalex.org\/W2755020525","https:\/\/openalex.org\/W2889089748","https:\/\/openalex.org\/W2895874513","https:\/\/openalex.org\/W3088045382","https:\/\/openalex.org\/W6639026721","https:\/\/openalex.org\/W6688435739"],"related_works":["https:\/\/openalex.org\/W2225046392","https:\/\/openalex.org\/W2628861693","https:\/\/openalex.org\/W4230044405","https:\/\/openalex.org\/W1979636863","https:\/\/openalex.org\/W3203087560","https:\/\/openalex.org\/W1605128151","https:\/\/openalex.org\/W945498656","https:\/\/openalex.org\/W4225648594","https:\/\/openalex.org\/W4387389613","https:\/\/openalex.org\/W1586180564"],"abstract_inverted_index":{"Perceptual":[0],"organization":[1],"is":[2],"the":[3,23,27,55,71,112],"process":[4,89],"of":[5,9,16,22,44,57,74,115],"assigning":[6],"each":[7],"part":[8,21],"a":[10,13,20,42,82,86,93,102],"scene":[11],"to":[12,18,37,97],"specified":[14],"association":[15],"features":[17,35,68],"be":[19,38],"same":[24],"organization.":[25],"In":[26,47],"twenty":[28],"century,":[29],"Gestalt":[30],"psychologists":[31],"formalized":[32],"how":[33],"image":[34],"tend":[36],"grouped":[39,69],"by":[40,70],"giving":[41],"set":[43],"organizing":[45],"principles.":[46],"this":[48],"paper,":[49],"we":[50],"propose":[51],"an":[52,61,78],"approach":[53],"for":[54],"detection":[56,114],"perceptual":[58,99,116],"groups":[59,100,117],"in":[60,67,101,118],"image.":[62],"We":[63,76,91],"are":[64],"mainly":[65],"interested":[66],"proximity":[72],"law":[73],"Gestalt.":[75],"conceive":[77],"object-based":[79],"model":[80,106],"within":[81],"stochastic":[83],"framework":[84],"using":[85],"marked":[87],"point":[88],"(MPP).":[90],"use":[92],"Bayesian":[94],"learning":[95],"method":[96],"extract":[98],"scene.":[103],"The":[104],"proposed":[105],"tested":[107],"on":[108],"synthetic":[109],"images":[110],"proves":[111],"efficient":[113],"noisy":[119],"images.":[120]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}