{"id":"https://openalex.org/W3147595824","doi":"https://doi.org/10.1109/lsp.2021.3070206","title":"Reliable Camera Model Identification Using Sparse Gaussian Processes","display_name":"Reliable Camera Model Identification Using Sparse Gaussian Processes","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3147595824","doi":"https://doi.org/10.1109/lsp.2021.3070206","mag":"3147595824"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2021.3070206","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2021.3070206","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":["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/A5008546345","display_name":"Benedikt Lorch","orcid":"https://orcid.org/0000-0002-7843-4656"},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Benedikt Lorch","raw_affiliation_strings":["IT Security Infrastructures Lab, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany"],"raw_orcid":"https://orcid.org/0000-0002-7843-4656","affiliations":[{"raw_affiliation_string":"IT Security Infrastructures Lab, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany","institution_ids":["https://openalex.org/I181369854"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069046837","display_name":"Franziska Schirrmacher","orcid":"https://orcid.org/0000-0003-1511-7669"},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Franziska Schirrmacher","raw_affiliation_strings":["IT Security Infrastructures Lab, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany"],"raw_orcid":"https://orcid.org/0000-0003-1511-7669","affiliations":[{"raw_affiliation_string":"IT Security Infrastructures Lab, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany","institution_ids":["https://openalex.org/I181369854"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073442830","display_name":"Anatol Maier","orcid":"https://orcid.org/0000-0002-8093-7252"},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Anatol Maier","raw_affiliation_strings":["IT Security Infrastructures Lab, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany"],"raw_orcid":"https://orcid.org/0000-0002-8093-7252","affiliations":[{"raw_affiliation_string":"IT Security Infrastructures Lab, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany","institution_ids":["https://openalex.org/I181369854"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049250339","display_name":"Christian Rie\u00df","orcid":"https://orcid.org/0000-0002-5556-5338"},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Christian Riess","raw_affiliation_strings":["IT Security Infrastructures Lab, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany"],"raw_orcid":"https://orcid.org/0000-0002-5556-5338","affiliations":[{"raw_affiliation_string":"IT Security Infrastructures Lab, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany","institution_ids":["https://openalex.org/I181369854"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I181369854"],"apc_list":null,"apc_paid":null,"fwci":0.9422,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.76361885,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"28","issue":null,"first_page":"912","last_page":"916"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","score":0.9998999834060669,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9998999834060669,"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/T12859","display_name":"Cell Image Analysis Techniques","score":0.9401999711990356,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9391000270843506,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.797382116317749},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7011988162994385},{"id":"https://openalex.org/keywords/global-positioning-system","display_name":"Global Positioning System","score":0.6362972855567932},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.592533528804779},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5493847131729126},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.52425217628479},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5149691700935364},{"id":"https://openalex.org/keywords/camera-auto-calibration","display_name":"Camera auto-calibration","score":0.5038098692893982},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4945637881755829},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.42223918437957764},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.3939652740955353},{"id":"https://openalex.org/keywords/camera-resectioning","display_name":"Camera resectioning","score":0.35790979862213135},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3553586006164551},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35526949167251587}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.797382116317749},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7011988162994385},{"id":"https://openalex.org/C60229501","wikidata":"https://www.wikidata.org/wiki/Q18822","display_name":"Global Positioning System","level":2,"score":0.6362972855567932},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.592533528804779},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5493847131729126},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.52425217628479},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5149691700935364},{"id":"https://openalex.org/C94816000","wikidata":"https://www.wikidata.org/wiki/Q5026006","display_name":"Camera auto-calibration","level":3,"score":0.5038098692893982},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4945637881755829},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.42223918437957764},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.3939652740955353},{"id":"https://openalex.org/C110898773","wikidata":"https://www.wikidata.org/wiki/Q2933935","display_name":"Camera resectioning","level":2,"score":0.35790979862213135},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3553586006164551},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35526949167251587},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsp.2021.3070206","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2021.3070206","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"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.7599999904632568}],"awards":[],"funders":[{"id":"https://openalex.org/F4320320879","display_name":"Deutsche Forschungsgemeinschaft","ror":"https://ror.org/018mejw64"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W137285897","https://openalex.org/W1032927584","https://openalex.org/W1092174439","https://openalex.org/W1506864492","https://openalex.org/W1520620701","https://openalex.org/W1533660737","https://openalex.org/W1587416387","https://openalex.org/W1663973292","https://openalex.org/W1746819321","https://openalex.org/W1968164921","https://openalex.org/W1979317425","https://openalex.org/W2009130368","https://openalex.org/W2049771774","https://openalex.org/W2068734928","https://openalex.org/W2072065288","https://openalex.org/W2084252081","https://openalex.org/W2122246182","https://openalex.org/W2124695272","https://openalex.org/W2154889936","https://openalex.org/W2174869877","https://openalex.org/W2528879890","https://openalex.org/W2553152707","https://openalex.org/W2561004319","https://openalex.org/W2594639291","https://openalex.org/W2756214248","https://openalex.org/W2890588722","https://openalex.org/W2893995718","https://openalex.org/W2938564271","https://openalex.org/W2963190151","https://openalex.org/W3100415668","https://openalex.org/W3133672610","https://openalex.org/W4211049957","https://openalex.org/W6605566567","https://openalex.org/W6631732945","https://openalex.org/W6755463424","https://openalex.org/W6783642298"],"related_works":["https://openalex.org/W2785097492","https://openalex.org/W2118427684","https://openalex.org/W2052984831","https://openalex.org/W2378222798","https://openalex.org/W2061162617","https://openalex.org/W2391933270","https://openalex.org/W227461850","https://openalex.org/W1503004767","https://openalex.org/W2392935764","https://openalex.org/W2160252628"],"abstract_inverted_index":{"Identifying":[0],"the":[1,23,126],"model":[2,130,159],"of":[3,32,128],"a":[4,29,39,60,78,96,102,135],"camera":[5,34,46,129,144,158],"that":[6,22,121],"has":[7],"captured":[8],"an":[9,13,44],"image":[10,24],"can":[11,41],"be":[12],"important":[14],"task":[15,127],"in":[16,106],"criminal":[17],"investigations.":[18],"Many":[19],"methods":[20],"assume":[21],"under":[25],"analysis":[26],"originates":[27],"from":[28,43,116,134],"given":[30],"set":[31],"known":[33,143],"models.":[35],"In":[36,58,84],"practice,":[37],"however,":[38],"photo":[40],"come":[42],"unknown":[45,56,82,117],"model,":[47],"or":[48],"its":[49],"appearance":[50],"could":[51],"have":[52],"been":[53],"altered":[54],"by":[55],"post-processing.":[57],"such":[59,95],"case,":[61],"forensic":[62,110],"detectors":[63],"are":[64],"prone":[65],"to":[66,71,76,125],"fail":[67],"silently.":[68],"One":[69],"way":[70],"mitigate":[72],"silent":[73],"failures":[74],"is":[75],"use":[77],"rejection":[79,97],"mechanism":[80],"for":[81,142],"examples.":[83],"this":[85],"work,":[86],"we":[87],"propose":[88],"Gaussian":[89],"processes":[90],"(GPs),":[91],"which":[92],"intrinsically":[93],"provide":[94],"mechanism.":[98],"This":[99],"makes":[100],"GPs":[101,122],"potentially":[103],"powerful":[104],"tool":[105],"multimedia":[107],"forensics,":[108],"where":[109],"analysts":[111],"regularly":[112],"work":[113],"on":[114],"images":[115],"origins.":[118],"We":[119],"demonstrate":[120],"scale":[123],"well":[124],"identification.":[131],"Probabilistic":[132],"predictions":[133],"GP":[136],"classifier":[137],"achieve":[138],"high":[139],"classification":[140],"accuracy":[141],"models":[145],"while":[146],"providing":[147],"reliable":[148],"uncertainty":[149,153],"estimates.":[150],"The":[151],"built-in":[152],"estimates":[154],"effectively":[155],"tackle":[156],"open-set":[157],"identification,":[160],"outperforming":[161],"two":[162],"state-of-the-art":[163],"methods.":[164]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}