{"id":"https://openalex.org/W2315899353","doi":"https://doi.org/10.1080/10798587.2016.1159059","title":"Particle filter planar target tracking with a monocular camera for mobile robots","display_name":"Particle filter planar target tracking with a monocular camera for mobile robots","publication_year":2016,"publication_date":"2016-03-21","ids":{"openalex":"https://openalex.org/W2315899353","doi":"https://doi.org/10.1080/10798587.2016.1159059","mag":"2315899353"},"language":"en","primary_location":{"id":"doi:10.1080/10798587.2016.1159059","is_oa":false,"landing_page_url":"https://doi.org/10.1080/10798587.2016.1159059","pdf_url":null,"source":{"id":"https://openalex.org/S40639465","display_name":"Intelligent Automation & Soft Computing","issn_l":"1079-8587","issn":["1079-8587","2326-005X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Automation &amp; Soft Computing","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/A5039660704","display_name":"Yu\u2010Cheng Chou","orcid":"https://orcid.org/0000-0002-9621-3638"},"institutions":[{"id":"https://openalex.org/I142974352","display_name":"National Sun Yat-sen University","ror":"https://ror.org/00mjawt10","country_code":"TW","type":"education","lineage":["https://openalex.org/I142974352"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Yu-Cheng Chou","raw_affiliation_strings":["Institute of Undersea Technology, National Sun Yat-sen University, Kaohsiung, Taiwan"],"affiliations":[{"raw_affiliation_string":"Institute of Undersea Technology, National Sun Yat-sen University, Kaohsiung, Taiwan","institution_ids":["https://openalex.org/I142974352"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040570107","display_name":"Madoka Nakajima","orcid":"https://orcid.org/0000-0002-8496-2973"},"institutions":[{"id":"https://openalex.org/I142974352","display_name":"National Sun Yat-sen University","ror":"https://ror.org/00mjawt10","country_code":"TW","type":"education","lineage":["https://openalex.org/I142974352"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Madoka Nakajima","raw_affiliation_strings":["Institute of Undersea Technology, National Sun Yat-sen University, Kaohsiung, Taiwan"],"affiliations":[{"raw_affiliation_string":"Institute of Undersea Technology, National Sun Yat-sen University, Kaohsiung, Taiwan","institution_ids":["https://openalex.org/I142974352"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5039660704"],"corresponding_institution_ids":["https://openalex.org/I142974352"],"apc_list":null,"apc_paid":null,"fwci":3.0525,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.91034528,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"23","issue":"1","first_page":"117","last_page":"125"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9983000159263611,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9980999827384949,"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":0.8700916767120361},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7660535573959351},{"id":"https://openalex.org/keywords/planar","display_name":"Planar","score":0.68943852186203},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.687117874622345},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6722329258918762},{"id":"https://openalex.org/keywords/particle-filter","display_name":"Particle filter","score":0.6080091595649719},{"id":"https://openalex.org/keywords/mobile-robot","display_name":"Mobile robot","score":0.5035912394523621},{"id":"https://openalex.org/keywords/monocular","display_name":"Monocular","score":0.4686813950538635},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.46088218688964844},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4499474763870239},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics (images)","score":0.3006429076194763}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8700916767120361},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7660535573959351},{"id":"https://openalex.org/C134786449","wikidata":"https://www.wikidata.org/wiki/Q3391255","display_name":"Planar","level":2,"score":0.68943852186203},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.687117874622345},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6722329258918762},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.6080091595649719},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.5035912394523621},{"id":"https://openalex.org/C65909025","wikidata":"https://www.wikidata.org/wiki/Q1945033","display_name":"Monocular","level":2,"score":0.4686813950538635},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.46088218688964844},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4499474763870239},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.3006429076194763},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/10798587.2016.1159059","is_oa":false,"landing_page_url":"https://doi.org/10.1080/10798587.2016.1159059","pdf_url":null,"source":{"id":"https://openalex.org/S40639465","display_name":"Intelligent Automation & Soft Computing","issn_l":"1079-8587","issn":["1079-8587","2326-005X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Automation &amp; Soft Computing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1513008779","https://openalex.org/W1513768190","https://openalex.org/W1591974398","https://openalex.org/W1990698117","https://openalex.org/W1991670922","https://openalex.org/W1998975250","https://openalex.org/W2005567888","https://openalex.org/W2008785834","https://openalex.org/W2025459463","https://openalex.org/W2029143333","https://openalex.org/W2059736897","https://openalex.org/W2075754515","https://openalex.org/W2080975376","https://openalex.org/W2082023026","https://openalex.org/W2092415663","https://openalex.org/W2097026069","https://openalex.org/W2098346313","https://openalex.org/W2105165852","https://openalex.org/W2113010291","https://openalex.org/W2145236880","https://openalex.org/W2150559602","https://openalex.org/W2157241873","https://openalex.org/W2158230879","https://openalex.org/W2158264856","https://openalex.org/W2159512980","https://openalex.org/W2160337655","https://openalex.org/W2169487039","https://openalex.org/W2236231320","https://openalex.org/W2461104673","https://openalex.org/W2986027862"],"related_works":["https://openalex.org/W1497101000","https://openalex.org/W2013820100","https://openalex.org/W2102101492","https://openalex.org/W2214805552","https://openalex.org/W2054021310","https://openalex.org/W2274330372","https://openalex.org/W2123824966","https://openalex.org/W3012261329","https://openalex.org/W2168494495","https://openalex.org/W2171669615"],"abstract_inverted_index":{"AbstractThis":[0],"paper":[1,72],"presents":[2],"an":[3],"effective":[4],"and":[5,67,80,96,104,126,145],"simple":[6],"target":[7,78,138],"tracking":[8,128],"approach":[9],"called":[10],"PSIPT":[11,27,114,132],"(Particle":[12],"filter":[13,44,60,120],"Single":[14],"Image":[15],"based":[16],"Planar":[17],"Target":[18],"tracking).":[19],"Compared":[20],"with":[21],"other":[22],"works,":[23],"the":[24,36,42,52,58,64,111,124,137],"uniqueness":[25],"of":[26,85],"includes:":[28],"(1)":[29,91],"only":[30],"a":[31,82,92,100,143],"single":[32],"color":[33],"camera":[34],"provides":[35],"images":[37],"to":[38,110],"be":[39],"processed;":[40],"(2)":[41,99],"particle":[43,59],"does":[45,61],"not":[46,62],"perform":[47],"data":[48],"fusion":[49],"calculations;":[50],"(3)":[51],"distance":[53,103],"evaluation":[54],"carried":[55],"out":[56],"in":[57,122,136],"need":[63],"camera\u2019s":[65],"intrinsic":[66],"extrinsic":[68],"parameters.":[69],"Meanwhile,":[70],"this":[71],"also":[73],"reveals":[74],"that,":[75],"under":[76],"different":[77],"shapes":[79],"cameras,":[81],"high":[83],"degree":[84],"negative":[86],"linear":[87],"dependence":[88],"remains":[89],"between:":[90],"target\u2019s":[93,101],"pixel":[94],"height":[95],"vertical":[97,102],"distance;":[98],"PWHD":[105],"(Pixel-Width-to-Horizontal":[106],"Distance)":[107],"ratio.":[108],"According":[109],"experimental":[112],"results,":[113],"performs":[115],"better":[116],"than":[117],"its":[118],"Kalman":[119],"variant":[121],"both":[123],"L-shape":[125],"S-shape":[127],"experiments.":[129],"In":[130],"addition,":[131],"has":[133],"moderate":[134],"performance":[135],"missing":[139],"surveillance":[140],"experiment.":[141],"Moreover,":[142],"hybrid":[144],"enhan...":[146]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
