{"id":"https://openalex.org/W3145390482","doi":"https://doi.org/10.1587/transfun.2020eal2111","title":"An Autoencoder Based Background Subtraction for Public Surveillance","display_name":"An Autoencoder Based Background Subtraction for Public Surveillance","publication_year":2021,"publication_date":"2021-04-07","ids":{"openalex":"https://openalex.org/W3145390482","doi":"https://doi.org/10.1587/transfun.2020eal2111","mag":"3145390482"},"language":"en","primary_location":{"id":"doi:10.1587/transfun.2020eal2111","is_oa":false,"landing_page_url":"https://doi.org/10.1587/transfun.2020eal2111","pdf_url":null,"source":{"id":"https://openalex.org/S166990724","display_name":"IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences","issn_l":"0916-8508","issn":["0916-8508","1745-1337"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4320800604","host_organization_name":"Institute of Electronics, Information and Communication Engineers","host_organization_lineage":["https://openalex.org/P4320800604"],"host_organization_lineage_names":["Institute of Electronics, Information and Communication Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences","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/A5100621538","display_name":"Yue Li","orcid":"https://orcid.org/0000-0001-5482-6244"},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yue LI","raw_affiliation_strings":["School of Humanities and Law, Northeastern University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Humanities and Law, Northeastern University","institution_ids":["https://openalex.org/I12912129"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073414420","display_name":"Xiaosheng Yu","orcid":"https://orcid.org/0000-0003-3218-1486"},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaosheng YU","raw_affiliation_strings":["Faculty of Robot Science and Engineering, Northeastern University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Robot Science and Engineering, Northeastern University","institution_ids":["https://openalex.org/I12912129"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111561664","display_name":"Haijun Cao","orcid":null},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Haijun CAO","raw_affiliation_strings":["School of Humanities and Law, Northeastern University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Humanities and Law, Northeastern University","institution_ids":["https://openalex.org/I12912129"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005083870","display_name":"Ming Xu","orcid":"https://orcid.org/0000-0002-4353-5449"},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ming XU","raw_affiliation_strings":["College of Information Science and Engineering, Northeastern University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering, Northeastern University","institution_ids":["https://openalex.org/I12912129"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I12912129"],"apc_list":null,"apc_paid":null,"fwci":0.1884,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.4526889,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"E104.A","issue":"10","first_page":"1445","last_page":"1449"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","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/T10331","display_name":"Video Surveillance and Tracking Methods","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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9873999953269958,"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"}},{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9868999719619751,"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/autoencoder","display_name":"Autoencoder","score":0.9829713702201843},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.733881950378418},{"id":"https://openalex.org/keywords/background-subtraction","display_name":"Background subtraction","score":0.7299506664276123},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5898817777633667},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5668696165084839},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5291281938552856},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4595670998096466},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4119621813297272},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.39385801553726196},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.20211726427078247},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.10658794641494751},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.09559980034828186}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.9829713702201843},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.733881950378418},{"id":"https://openalex.org/C32653426","wikidata":"https://www.wikidata.org/wiki/Q3813641","display_name":"Background subtraction","level":3,"score":0.7299506664276123},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5898817777633667},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5668696165084839},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5291281938552856},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4595670998096466},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4119621813297272},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.39385801553726196},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.20211726427078247},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.10658794641494751},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.09559980034828186}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1587/transfun.2020eal2111","is_oa":false,"landing_page_url":"https://doi.org/10.1587/transfun.2020eal2111","pdf_url":null,"source":{"id":"https://openalex.org/S166990724","display_name":"IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences","issn_l":"0916-8508","issn":["0916-8508","1745-1337"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4320800604","host_organization_name":"Institute of Electronics, Information and Communication Engineers","host_organization_lineage":["https://openalex.org/P4320800604"],"host_organization_lineage_names":["Institute of Electronics, Information and Communication Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences","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":0.5}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W600850598","https://openalex.org/W1525699417","https://openalex.org/W1964127768","https://openalex.org/W1980757516","https://openalex.org/W1994634851","https://openalex.org/W2040645214","https://openalex.org/W2067764400","https://openalex.org/W2067813398","https://openalex.org/W2073237885","https://openalex.org/W2102625004","https://openalex.org/W2127070222","https://openalex.org/W2168408594","https://openalex.org/W2394875178","https://openalex.org/W2525668722","https://openalex.org/W2624386319","https://openalex.org/W2759692151","https://openalex.org/W2783946051","https://openalex.org/W4248936881","https://openalex.org/W4300179783"],"related_works":["https://openalex.org/W3013693939","https://openalex.org/W2159052453","https://openalex.org/W2566616303","https://openalex.org/W3131327266","https://openalex.org/W4297051394","https://openalex.org/W2752972570","https://openalex.org/W2734887215","https://openalex.org/W2803255133","https://openalex.org/W2669956259","https://openalex.org/W4249005693"],"abstract_inverted_index":{"An":[0],"autoencoder":[1,39],"is":[2],"trained":[3],"to":[4,48],"generate":[5],"the":[6,9,14,18,23,31,41,45],"background":[7,47],"from":[8,40],"surveillance":[10,42],"image":[11,43],"by":[12,36],"setting":[13],"training":[15],"label":[16],"as":[17],"shuffled":[19],"input,":[20],"instead":[21],"of":[22],"input":[24],"itself":[25],"in":[26],"a":[27,37],"traditional":[28],"autoencoder.":[29],"Then":[30],"multi-scale":[32],"features":[33],"are":[34],"extracted":[35],"sparse":[38],"and":[44],"corresponding":[46],"detect":[49],"foreground.":[50]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
