{"id":"https://openalex.org/W2564504769","doi":"https://doi.org/10.1145/3009977.3010059","title":"Spatio-temporal weighted histogram based mean shift for illumination robust target tracking","display_name":"Spatio-temporal weighted histogram based mean shift for illumination robust target tracking","publication_year":2016,"publication_date":"2016-12-18","ids":{"openalex":"https://openalex.org/W2564504769","doi":"https://doi.org/10.1145/3009977.3010059","mag":"2564504769"},"language":"en","primary_location":{"id":"doi:10.1145/3009977.3010059","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3009977.3010059","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Tenth Indian Conference on Computer Vision, Graphics and Image Processing","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/A5076062190","display_name":"Kalyani Deopujari","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Kalyani Deopujari","raw_affiliation_strings":["MES College of Engineering, Pune, India"],"affiliations":[{"raw_affiliation_string":"MES College of Engineering, Pune, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103090020","display_name":"Rajbabu Velmurugan","orcid":"https://orcid.org/0000-0002-3511-1806"},"institutions":[{"id":"https://openalex.org/I162827531","display_name":"Indian Institute of Technology Bombay","ror":"https://ror.org/02qyf5152","country_code":"IN","type":"education","lineage":["https://openalex.org/I162827531"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Rajbabu Velmurugan","raw_affiliation_strings":["Indian Institute of Technology Bombay, Mumbai, India"],"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology Bombay, Mumbai, India","institution_ids":["https://openalex.org/I162827531"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068873012","display_name":"Kanchan S. Tiwari","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kanchan Tiwari","raw_affiliation_strings":["MES College of Engineering, Pune, India"],"affiliations":[{"raw_affiliation_string":"MES College of Engineering, Pune, India","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5076062190"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.14429322,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9907000064849854,"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/T11439","display_name":"Video Analysis and Summarization","score":0.9523000121116638,"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/discrete-cosine-transform","display_name":"Discrete cosine transform","score":0.716411828994751},{"id":"https://openalex.org/keywords/mean-shift","display_name":"Mean-shift","score":0.6849649548530579},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.6842800974845886},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6781134009361267},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6283724308013916},{"id":"https://openalex.org/keywords/bittorrent-tracker","display_name":"BitTorrent tracker","score":0.6232149600982666},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5195958614349365},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5190032720565796},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.49607428908348083},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.44422945380210876},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.20852217078208923},{"id":"https://openalex.org/keywords/eye-tracking","display_name":"Eye tracking","score":0.11823943257331848}],"concepts":[{"id":"https://openalex.org/C2221639","wikidata":"https://www.wikidata.org/wiki/Q2877","display_name":"Discrete cosine transform","level":3,"score":0.716411828994751},{"id":"https://openalex.org/C48548287","wikidata":"https://www.wikidata.org/wiki/Q6803557","display_name":"Mean-shift","level":3,"score":0.6849649548530579},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.6842800974845886},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6781134009361267},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6283724308013916},{"id":"https://openalex.org/C57501372","wikidata":"https://www.wikidata.org/wiki/Q2021268","display_name":"BitTorrent tracker","level":3,"score":0.6232149600982666},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5195958614349365},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5190032720565796},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.49607428908348083},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.44422945380210876},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.20852217078208923},{"id":"https://openalex.org/C56461940","wikidata":"https://www.wikidata.org/wiki/Q970687","display_name":"Eye tracking","level":2,"score":0.11823943257331848},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","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:10.1145/3009977.3010059","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3009977.3010059","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Tenth Indian Conference on Computer Vision, Graphics and Image Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.8399999737739563}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W182940129","https://openalex.org/W1533162639","https://openalex.org/W1595217348","https://openalex.org/W1642351821","https://openalex.org/W1955741794","https://openalex.org/W1992718502","https://openalex.org/W1995538671","https://openalex.org/W1997121481","https://openalex.org/W2000158197","https://openalex.org/W2089961441","https://openalex.org/W2098854771","https://openalex.org/W2101372036","https://openalex.org/W2108215708","https://openalex.org/W2109579504","https://openalex.org/W2121121722","https://openalex.org/W2130026429","https://openalex.org/W2132103241","https://openalex.org/W2133001582","https://openalex.org/W2137330118","https://openalex.org/W2139047213","https://openalex.org/W2159128898","https://openalex.org/W2165037244","https://openalex.org/W2167089254","https://openalex.org/W2343187456","https://openalex.org/W3102624093","https://openalex.org/W6675197054"],"related_works":["https://openalex.org/W2023748438","https://openalex.org/W2124385053","https://openalex.org/W1916685473","https://openalex.org/W2055682261","https://openalex.org/W2169903804","https://openalex.org/W2352790313","https://openalex.org/W1618706760","https://openalex.org/W2057178930","https://openalex.org/W72160640","https://openalex.org/W106298641"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3,11,74],"simple":[4],"method":[5,15,43,118,135,148],"to":[6,33,52,55,84],"handle":[7,34],"illumination":[8,35,72,77,93,124],"variation":[9,36],"in":[10,60,71],"video.":[12],"The":[13,41,63,99,116,126,166],"proposed":[14,42,64,117,134,155,171],"is":[16],"based":[17,50,147],"on":[18,109],"generative":[19],"mean":[20,61],"shift":[21],"tracker,":[22],"which":[23],"uses":[24,44],"energy":[25],"compaction":[26],"property":[27],"of":[28,69,79,132,162],"discrete":[29],"Cosine":[30],"transform":[31],"(DCT)":[32],"within":[37,73],"and":[38,46,57,86,107,113,128,149],"across":[39,88],"frames.":[40],"spatial":[45],"temporal":[47],"DCT":[48,145],"coefficient":[49,146],"approach":[51],"assign":[53],"weights":[54],"target":[56,81],"candidate":[58],"histograms":[59],"shift.":[62],"weighing":[65],"factor":[66],"takes":[67],"care":[68],"changes":[70],"frame":[75],"i.e.,":[76,91],"change":[78],"the":[80,89,95,133,139,154,163,170],"with":[82,143,159,178],"respect":[83],"background":[85],"also":[87,108,120],"frames":[90],"varying":[92],"between":[94],"consecutive":[96],"time":[97],"instances.":[98],"algorithm":[100,156,172],"was":[101,119,136,141,157],"tested":[102,121],"using":[103],"VOT2015":[104],"challenge":[105],"dataset":[106],"sequences":[110],"from":[111],"OTB":[112],"CAVIAR":[114],"datasets.":[115],"rigorously":[122],"for":[123],"attribute.":[125],"qualitative":[127],"quantitative":[129],"evaluation":[130],"process":[131],"twofold.":[137],"First,":[138],"tracker":[140],"compared":[142,158],"existing":[144],"showed":[150,181],"improved":[151],"results.":[152],"Secondly,":[153],"other":[160],"state":[161],"art":[164],"trackers.":[165],"results":[167],"show":[168],"that":[169],"outperformed":[173],"some":[174],"state-of-the-art":[175],"trackers":[176],"while":[177],"others":[179],"it":[180],"comparable":[182],"performance.":[183]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
