{"id":"https://openalex.org/W2940797985","doi":"https://doi.org/10.1109/tits.2019.2909915","title":"Moving Object Detection Through Image Bit-Planes Representation Without Thresholding","display_name":"Moving Object Detection Through Image Bit-Planes Representation Without Thresholding","publication_year":2019,"publication_date":"2019-04-25","ids":{"openalex":"https://openalex.org/W2940797985","doi":"https://doi.org/10.1109/tits.2019.2909915","mag":"2940797985"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2019.2909915","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2019.2909915","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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 Transactions on Intelligent Transportation Systems","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/A5087964642","display_name":"Chih\u2010Yang Lin","orcid":"https://orcid.org/0000-0002-0401-8473"},"institutions":[{"id":"https://openalex.org/I99908691","display_name":"Yuan Ze University","ror":"https://ror.org/01fv1ds98","country_code":"TW","type":"education","lineage":["https://openalex.org/I99908691"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chih-Yang Lin","raw_affiliation_strings":["Yuan Ze University, Taoyuan, Taiwan"],"raw_orcid":"https://orcid.org/0000-0002-0401-8473","affiliations":[{"raw_affiliation_string":"Yuan Ze University, Taoyuan, Taiwan","institution_ids":["https://openalex.org/I99908691"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089411412","display_name":"Kahlil Muchtar","orcid":"https://orcid.org/0000-0001-5740-1938"},"institutions":[{"id":"https://openalex.org/I187494767","display_name":"Universitas Syiah Kuala","ror":"https://ror.org/05v4dza81","country_code":"ID","type":"education","lineage":["https://openalex.org/I187494767"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Kahlil Muchtar","raw_affiliation_strings":["Nodeflux, Jakarta, Indonesia","Syiah Kuala University, Aceh, Indonesia"],"raw_orcid":"https://orcid.org/0000-0001-5740-1938","affiliations":[{"raw_affiliation_string":"Nodeflux, Jakarta, Indonesia","institution_ids":[]},{"raw_affiliation_string":"Syiah Kuala University, Aceh, Indonesia","institution_ids":["https://openalex.org/I187494767"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101420358","display_name":"Wei-Yang Lin","orcid":"https://orcid.org/0000-0003-0895-2498"},"institutions":[{"id":"https://openalex.org/I148099254","display_name":"National Chung Cheng University","ror":"https://ror.org/0028v3876","country_code":"TW","type":"education","lineage":["https://openalex.org/I148099254"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Wei-Yang Lin","raw_affiliation_strings":["National Chung Cheng University, Chiayi, Taiwan"],"raw_orcid":"https://orcid.org/0000-0003-0895-2498","affiliations":[{"raw_affiliation_string":"National Chung Cheng University, Chiayi, Taiwan","institution_ids":["https://openalex.org/I148099254"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068704225","display_name":"Zhi-Yao Jian","orcid":null},"institutions":[{"id":"https://openalex.org/I148099254","display_name":"National Chung Cheng University","ror":"https://ror.org/0028v3876","country_code":"TW","type":"education","lineage":["https://openalex.org/I148099254"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Zhi-Yao Jian","raw_affiliation_strings":["National Chung Cheng University, Chiayi, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Chung Cheng University, Chiayi, Taiwan","institution_ids":["https://openalex.org/I148099254"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.3606,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":{"value":0.81722862,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"21","issue":"4","first_page":"1404","last_page":"1414"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","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/T10331","display_name":"Video Surveillance and Tracking Methods","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":0.9976000189781189,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9968000054359436,"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/background-subtraction","display_name":"Background subtraction","score":0.8608536124229431},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8161267638206482},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.757839560508728},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.7402647733688354},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7391766309738159},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6803684234619141},{"id":"https://openalex.org/keywords/brightness","display_name":"Brightness","score":0.5929204821586609},{"id":"https://openalex.org/keywords/shadow","display_name":"Shadow (psychology)","score":0.5693684220314026},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4842802882194519},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4620596170425415},{"id":"https://openalex.org/keywords/foreground-detection","display_name":"Foreground detection","score":0.4310973882675171},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4020167589187622},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3231773376464844},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.27461308240890503}],"concepts":[{"id":"https://openalex.org/C32653426","wikidata":"https://www.wikidata.org/wiki/Q3813641","display_name":"Background subtraction","level":3,"score":0.8608536124229431},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8161267638206482},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.757839560508728},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.7402647733688354},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7391766309738159},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6803684234619141},{"id":"https://openalex.org/C125245961","wikidata":"https://www.wikidata.org/wiki/Q221656","display_name":"Brightness","level":2,"score":0.5929204821586609},{"id":"https://openalex.org/C117797892","wikidata":"https://www.wikidata.org/wiki/Q286363","display_name":"Shadow (psychology)","level":2,"score":0.5693684220314026},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4842802882194519},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4620596170425415},{"id":"https://openalex.org/C2779769447","wikidata":"https://www.wikidata.org/wiki/Q3813641","display_name":"Foreground detection","level":4,"score":0.4310973882675171},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4020167589187622},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3231773376464844},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.27461308240890503},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C542102704","wikidata":"https://www.wikidata.org/wiki/Q183257","display_name":"Psychotherapist","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2019.2909915","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2019.2909915","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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 Transactions on Intelligent Transportation Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6800000071525574,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[{"id":"https://openalex.org/G561600775","display_name":"Head-Shoulder Detection Based on Template Matching and Deep Learning","funder_award_id":"MOST106-2221-E155-070","funder_id":"https://openalex.org/F4320322795","funder_display_name":"Ministry of Science and Technology, Taiwan"},{"id":"https://openalex.org/G7650704033","display_name":"Software Development in 3d Modeling and Manipulation for Precisely Clinical Applications( III )","funder_award_id":"MOST106-2218-E468-001","funder_id":"https://openalex.org/F4320322795","funder_display_name":"Ministry of Science and Technology, Taiwan"},{"id":"https://openalex.org/G7882981651","display_name":"The Intelligent Parter of the Blind( II )","funder_award_id":"MOST108-2634-F008-001","funder_id":"https://openalex.org/F4320322795","funder_display_name":"Ministry of Science and Technology, Taiwan"},{"id":"https://openalex.org/G7980458236","display_name":"The Research of Automatic Surface Defect Detection for Industrial Applications Based on Deep Learning","funder_award_id":"MOST107-2221-E155-048-MY3","funder_id":"https://openalex.org/F4320322795","funder_display_name":"Ministry of Science and Technology, Taiwan"}],"funders":[{"id":"https://openalex.org/F4320322795","display_name":"Ministry of Science and Technology, Taiwan","ror":"https://ror.org/02kv4zf79"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W1485168651","https://openalex.org/W1509589980","https://openalex.org/W1587895281","https://openalex.org/W1923940912","https://openalex.org/W1969977005","https://openalex.org/W2007057886","https://openalex.org/W2020388530","https://openalex.org/W2020999234","https://openalex.org/W2023536220","https://openalex.org/W2061051600","https://openalex.org/W2065301447","https://openalex.org/W2074157064","https://openalex.org/W2084944437","https://openalex.org/W2088117572","https://openalex.org/W2102625004","https://openalex.org/W2113137767","https://openalex.org/W2113708607","https://openalex.org/W2119300483","https://openalex.org/W2120804060","https://openalex.org/W2124351162","https://openalex.org/W2126789858","https://openalex.org/W2127070222","https://openalex.org/W2140235142","https://openalex.org/W2142290030","https://openalex.org/W2143516773","https://openalex.org/W2169551590","https://openalex.org/W2485576322","https://openalex.org/W2507402573","https://openalex.org/W2538864697","https://openalex.org/W2589036197","https://openalex.org/W2713774261","https://openalex.org/W2751850814","https://openalex.org/W2764012408","https://openalex.org/W2914976302","https://openalex.org/W4230354037","https://openalex.org/W4300179783","https://openalex.org/W6630258437"],"related_works":["https://openalex.org/W2105103921","https://openalex.org/W2086414697","https://openalex.org/W1999137714","https://openalex.org/W2953123162","https://openalex.org/W2188430267","https://openalex.org/W4298195641","https://openalex.org/W2110416663","https://openalex.org/W3010714307","https://openalex.org/W2123129869","https://openalex.org/W1987287817"],"abstract_inverted_index":{"Background":[0],"subtraction":[1],"is":[2,60],"an":[3],"example":[4],"of":[5,100,105],"a":[6,35,44,97],"moving":[7,17],"object":[8,18],"detection":[9,19,101],"technique":[10],"that":[11,91],"uses":[12],"machine":[13],"vision":[14],"systems.":[15],"Conventional":[16],"methods":[20],"need":[21],"complicated":[22],"thresholds":[23],"for":[24,65],"background":[25,37],"modeling":[26,38],"to":[27],"address":[28],"changes":[29],"in":[30],"illumination.":[31],"This":[32],"paper":[33],"proposes":[34],"novel":[36],"approach":[39],"without":[40],"thresholding":[41],"based":[42],"on":[43],"bit-planes":[45],"method,":[46],"which":[47],"fully":[48],"utilizes":[49],"color":[50],"characteristics":[51],"through":[52],"spatial":[53],"and":[54,62,68,80],"temporal-based":[55],"improvement.":[56],"The":[57,88],"proposed":[58,74,93],"idea":[59,94],"effective":[61],"efficiently":[63],"solving":[64],"shadow":[66],"disturbance":[67],"brightness":[69],"changes.":[70],"We":[71],"evaluate":[72],"our":[73],"method":[75],"using":[76],"several":[77],"challenging":[78],"indoor":[79],"outdoor":[81],"sequences":[82],"from":[83],"the":[84,92,106],"CDNET":[85],"2014":[86],"dataset.":[87],"experiments":[89],"show":[90],"typically":[95],"achieves":[96],"higher":[98],"rate":[99],"accuracy":[102],"than":[103],"those":[104],"current":[107],"state-of-the-art":[108],"approaches.":[109]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":2}],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2025-10-10T00:00:00"}
