{"id":"https://openalex.org/W2491745890","doi":"https://doi.org/10.1109/rait.2016.7507942","title":"Color based human detection and tracking algorithm using a non-Gaussian adaptive Particle filter","display_name":"Color based human detection and tracking algorithm using a non-Gaussian adaptive Particle filter","publication_year":2016,"publication_date":"2016-03-01","ids":{"openalex":"https://openalex.org/W2491745890","doi":"https://doi.org/10.1109/rait.2016.7507942","mag":"2491745890"},"language":"en","primary_location":{"id":"doi:10.1109/rait.2016.7507942","is_oa":false,"landing_page_url":"https://doi.org/10.1109/rait.2016.7507942","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 3rd International Conference on Recent Advances in Information Technology (RAIT)","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/A5068773651","display_name":"Aashish Sharma","orcid":"https://orcid.org/0000-0001-9211-3368"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Aashish Sharma","raw_affiliation_strings":["Freescale Semiconductors India (NXP group of companies)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Freescale Semiconductors India (NXP group of companies)","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100719292","display_name":"Ajay Kumar Singh","orcid":"https://orcid.org/0000-0001-6160-8376"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ajay Singh","raw_affiliation_strings":["Nvidia, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nvidia, India","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101698273","display_name":"Rajesh Rohilla","orcid":"https://orcid.org/0000-0003-4513-0338"},"institutions":[{"id":"https://openalex.org/I863896202","display_name":"Delhi Technological University","ror":"https://ror.org/01ztcvt22","country_code":"IN","type":"education","lineage":["https://openalex.org/I863896202"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Rajesh Rohilla","raw_affiliation_strings":["Dept. of Electronics and Communication Engineering, Delhi Technological University, Delhi"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Electronics and Communication Engineering, Delhi Technological University, Delhi","institution_ids":["https://openalex.org/I863896202"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.338,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.66085769,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"6","issue":null,"first_page":"439","last_page":"442"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9998000264167786,"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":0.9998000264167786,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.980400025844574,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9643999934196472,"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/particle-filter","display_name":"Particle filter","score":0.8697879314422607},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.6703615188598633},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6350330114364624},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5803202390670776},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5646883845329285},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5439969301223755},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5294399261474609},{"id":"https://openalex.org/keywords/adaptive-filter","display_name":"Adaptive filter","score":0.5265731811523438},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.48711276054382324},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.46115589141845703},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.4536811411380768},{"id":"https://openalex.org/keywords/kernel-adaptive-filter","display_name":"Kernel adaptive filter","score":0.44545063376426697},{"id":"https://openalex.org/keywords/monte-carlo-localization","display_name":"Monte Carlo localization","score":0.4350528120994568},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.43014806509017944},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2515838146209717},{"id":"https://openalex.org/keywords/filter-design","display_name":"Filter design","score":0.20770689845085144},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.11290493607521057},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.0779924988746643}],"concepts":[{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.8697879314422607},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.6703615188598633},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6350330114364624},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5803202390670776},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5646883845329285},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5439969301223755},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5294399261474609},{"id":"https://openalex.org/C102248274","wikidata":"https://www.wikidata.org/wiki/Q168388","display_name":"Adaptive filter","level":2,"score":0.5265731811523438},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.48711276054382324},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.46115589141845703},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.4536811411380768},{"id":"https://openalex.org/C13107197","wikidata":"https://www.wikidata.org/wiki/Q6394192","display_name":"Kernel adaptive filter","level":4,"score":0.44545063376426697},{"id":"https://openalex.org/C106480740","wikidata":"https://www.wikidata.org/wiki/Q6904694","display_name":"Monte Carlo localization","level":4,"score":0.4350528120994568},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.43014806509017944},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2515838146209717},{"id":"https://openalex.org/C22597639","wikidata":"https://www.wikidata.org/wiki/Q5449227","display_name":"Filter design","level":3,"score":0.20770689845085144},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.11290493607521057},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0779924988746643},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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},{"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:10.1109/rait.2016.7507942","is_oa":false,"landing_page_url":"https://doi.org/10.1109/rait.2016.7507942","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 3rd International Conference on Recent Advances in Information Technology (RAIT)","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":12,"referenced_works":["https://openalex.org/W1673002162","https://openalex.org/W1974539925","https://openalex.org/W1995903777","https://openalex.org/W2051628223","https://openalex.org/W2109609054","https://openalex.org/W2123736354","https://openalex.org/W2143176742","https://openalex.org/W2153864854","https://openalex.org/W2160337655","https://openalex.org/W6637398742","https://openalex.org/W6676208019","https://openalex.org/W6678466122"],"related_works":["https://openalex.org/W2128655648","https://openalex.org/W1518703880","https://openalex.org/W1837108749","https://openalex.org/W2165929034","https://openalex.org/W2134351344","https://openalex.org/W3147794891","https://openalex.org/W1968683859","https://openalex.org/W2138031790","https://openalex.org/W1992775103","https://openalex.org/W2015530857"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"an":[3,39],"algorithm":[4,103,132],"is":[5,38,57,124],"presented":[6],"that":[7,61,71],"can":[8,77],"detect":[9],"and":[10,24,48,66,80,87,91,114,121,133],"isolate":[11],"moving":[12],"skin":[13,111],"colored":[14],"pixels,":[15],"or":[16],"more":[17,79,81],"generally":[18],"humans,":[19],"from":[20],"a":[21,29,134],"static":[22],"background,":[23],"then":[25],"track":[26],"them":[27],"using":[28],"non-Gaussian":[30],"recursive":[31],"Bayesian":[32],"Particle":[33,35,115],"filter.":[34],"filter":[36,41,116],"(PF)":[37],"adaptive":[40],"based":[42],"on":[43],"sequential":[44],"Monte":[45],"Carlo":[46],"methods,":[47],"represents":[49],"probability":[50],"densities":[51],"in":[52],"terms":[53],"of":[54,58,64,100,129],"particles.":[55],"It":[56],"vital":[59],"importance":[60],"the":[62,72,84,89,127],"elements":[63],"non-linearity":[65],"non-Gaussianity":[67],"are":[68],"included":[69],"so":[70],"physical":[73],"system":[74],"being":[75],"modeled":[76],"be":[78],"close":[82],"to":[83],"real":[85],"world,":[86],"all":[88],"estimations":[90],"analysis":[92],"carried":[93],"out":[94],"could":[95],"hold":[96],"practical.":[97],"Key":[98],"aspects":[99],"our":[101,130],"tracking":[102,131],"such":[104],"as":[105],"background":[106],"removal":[107],"with":[108],"illumination":[109],"compensation,":[110],"color":[112],"detection":[113],"implementation":[117],"have":[118],"been":[119],"explained":[120],"demonstrated.":[122],"This":[123],"followed":[125],"by":[126],"results":[128],"conclusion.":[135]},"counts_by_year":[{"year":2018,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}