{"id":"https://openalex.org/W2295767834","doi":"https://doi.org/10.1109/icip.2015.7351367","title":"Double layer salient parts based multi-people tracking","display_name":"Double layer salient parts based multi-people tracking","publication_year":2015,"publication_date":"2015-09-01","ids":{"openalex":"https://openalex.org/W2295767834","doi":"https://doi.org/10.1109/icip.2015.7351367","mag":"2295767834"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2015.7351367","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2015.7351367","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Image Processing (ICIP)","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/A5100760222","display_name":"Zhi Zhou","orcid":"https://orcid.org/0000-0002-9142-8146"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Zhi Zhou","raw_affiliation_strings":["Nanyang Technological University School of Electrical and Electronic Engineering Singapore, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanyang Technological University School of Electrical and Electronic Engineering Singapore, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100372051","display_name":"Yue Wang","orcid":"https://orcid.org/0000-0002-6315-7625"},"institutions":[{"id":"https://openalex.org/I3005327000","display_name":"Institute for Infocomm Research","ror":"https://ror.org/053rfa017","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I3005327000","https://openalex.org/I91275662"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Yue Wang","raw_affiliation_strings":["Institute for Infocomm Research (I2R) Visual Computing Department Singapore, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Infocomm Research (I2R) Visual Computing Department Singapore, Singapore","institution_ids":["https://openalex.org/I3005327000"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111838060","display_name":"Eam Khwang Teoh","orcid":null},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Eam Khwang Teoh","raw_affiliation_strings":["Nanyang Technological University School of Electrical and Electronic Engineering Singapore, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanyang Technological University School of Electrical and Electronic Engineering Singapore, Singapore","institution_ids":["https://openalex.org/I172675005"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1837,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.6129509,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"3067","last_page":"3071"},"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9961000084877014,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.995199978351593,"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/salient","display_name":"Salient","score":0.8705213665962219},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.7690358757972717},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7252341508865356},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6703301668167114},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6369374990463257},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5579746961593628},{"id":"https://openalex.org/keywords/data-association","display_name":"Data association","score":0.5493285059928894},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.5305341482162476},{"id":"https://openalex.org/keywords/association","display_name":"Association (psychology)","score":0.47331535816192627},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.44119614362716675},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.4403115510940552},{"id":"https://openalex.org/keywords/tracking-system","display_name":"Tracking system","score":0.41781747341156006},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36595290899276733},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.2462257444858551},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.09218165278434753},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.061847418546676636}],"concepts":[{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.8705213665962219},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.7690358757972717},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7252341508865356},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6703301668167114},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6369374990463257},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5579746961593628},{"id":"https://openalex.org/C2983325608","wikidata":"https://www.wikidata.org/wiki/Q17084606","display_name":"Data association","level":3,"score":0.5493285059928894},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.5305341482162476},{"id":"https://openalex.org/C142853389","wikidata":"https://www.wikidata.org/wiki/Q744778","display_name":"Association (psychology)","level":2,"score":0.47331535816192627},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.44119614362716675},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.4403115510940552},{"id":"https://openalex.org/C154586513","wikidata":"https://www.wikidata.org/wiki/Q4420972","display_name":"Tracking system","level":3,"score":0.41781747341156006},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36595290899276733},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.2462257444858551},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.09218165278434753},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.061847418546676636},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","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/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/icip.2015.7351367","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2015.7351367","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1825108226","https://openalex.org/W1986426688","https://openalex.org/W1987389530","https://openalex.org/W1997500560","https://openalex.org/W2016135469","https://openalex.org/W2029742464","https://openalex.org/W2035153336","https://openalex.org/W2047286693","https://openalex.org/W2055022211","https://openalex.org/W2061773916","https://openalex.org/W2068335629","https://openalex.org/W2083049794","https://openalex.org/W2118740913","https://openalex.org/W2128272608","https://openalex.org/W2130258433","https://openalex.org/W2134529534","https://openalex.org/W2138302688","https://openalex.org/W2141822239","https://openalex.org/W2146183743","https://openalex.org/W2148958980","https://openalex.org/W2158634074","https://openalex.org/W2161969291","https://openalex.org/W2165737454","https://openalex.org/W2168356304","https://openalex.org/W2171243491","https://openalex.org/W2222512263","https://openalex.org/W2398033114","https://openalex.org/W3120048558","https://openalex.org/W6638356639","https://openalex.org/W6659566489","https://openalex.org/W6665973531","https://openalex.org/W6667782953"],"related_works":["https://openalex.org/W2329500892","https://openalex.org/W28991112","https://openalex.org/W2370726991","https://openalex.org/W2369710579","https://openalex.org/W4327728159","https://openalex.org/W4394266730","https://openalex.org/W1568122762","https://openalex.org/W853822470","https://openalex.org/W621585789","https://openalex.org/W2152713066"],"abstract_inverted_index":{"Multi-people":[0],"tracking":[1,26,70,102],"has":[2],"been":[3],"studied":[4],"for":[5,113],"decades.":[6],"It":[7,39],"is":[8,33,40,74,111],"already":[9],"applied":[10,75],"in":[11,45],"many":[12],"computer":[13],"vision":[14],"tasks.":[15],"In":[16],"this":[17,46],"paper,":[18],"the":[19,51,58,63,86,95,101,127,134,138],"proposed":[20,128,139],"framework":[21],"performs":[22],"frame":[23,25],"to":[24,35,93,125],"and":[27],"follows":[28],"tracking-by-detection":[29],"approach.":[30],"Saliency":[31],"detection":[32],"introduced":[34],"enhance":[36],"multi-people":[37],"tracking.":[38],"performed":[41],"on":[42,100,121],"two":[43],"layers":[44],"method.":[47,129],"Salient":[48],"parts":[49,61,73],"inside":[50],"human":[52],"patch":[53],"denote":[54],"representative":[55],"regions":[56],"of":[57,71,97,104,137],"target,":[59],"while":[60],"around":[62],"target":[64],"capture":[65],"context":[66],"information.":[67],"Short":[68],"term":[69],"salient":[72,105],"along":[76],"with":[77,83,142],"data":[78,81],"association.":[79],"When":[80],"association":[82],"detections":[84],"fails,":[85],"supporting":[87],"models":[88],"on-line":[89],"learned":[90],"are":[91,118],"used":[92,112],"indicate":[94],"locations":[96],"targets":[98],"based":[99,109],"results":[103,132],"parts.":[106],"A":[107],"Bayesian":[108],"method":[110,140],"mutual":[114],"occlusion":[115],"reasoning.":[116],"Experiments":[117],"carried":[119],"out":[120],"several":[122],"public":[123],"datasets":[124],"evaluate":[126],"The":[130],"experimental":[131],"show":[133],"promising":[135],"performance":[136],"compared":[141],"state-of-the-art":[143],"works.":[144]},"counts_by_year":[{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}