{"id":"https://openalex.org/W2152565647","doi":"https://doi.org/10.1145/2675744.2675748","title":"Motion segmentation from surveillance videos using T-test statistics","display_name":"Motion segmentation from surveillance videos using T-test statistics","publication_year":2014,"publication_date":"2014-10-09","ids":{"openalex":"https://openalex.org/W2152565647","doi":"https://doi.org/10.1145/2675744.2675748","mag":"2152565647"},"language":"en","primary_location":{"id":"doi:10.1145/2675744.2675748","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2675744.2675748","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 7th ACM India Computing Conference","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/A5113369872","display_name":"M. Chandrajit","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Chandrajit M","raw_affiliation_strings":["MIT, Mysore"],"affiliations":[{"raw_affiliation_string":"MIT, Mysore","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029279237","display_name":"R. Girisha","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Girisha R","raw_affiliation_strings":["PESCE, Mandya"],"affiliations":[{"raw_affiliation_string":"PESCE, Mandya","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017751885","display_name":"T Vasudev","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Vasudev T","raw_affiliation_strings":["MIT, Mysore"],"affiliations":[{"raw_affiliation_string":"MIT, Mysore","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5113369872"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.7316,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.77200966,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"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/T10531","display_name":"Advanced Vision and Imaging","score":0.998199999332428,"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9959999918937683,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7969120740890503},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7955115437507629},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7115017771720886},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6609101295471191},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.5611936450004578},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4655504822731018},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.42728516459465027},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.4179636240005493},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.414916455745697},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.15199041366577148}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7969120740890503},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7955115437507629},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7115017771720886},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6609101295471191},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.5611936450004578},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4655504822731018},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.42728516459465027},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.4179636240005493},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.414916455745697},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.15199041366577148}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2675744.2675748","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2675744.2675748","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 7th ACM India Computing Conference","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.7200000286102295}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W25447271","https://openalex.org/W179630507","https://openalex.org/W604112557","https://openalex.org/W1517679084","https://openalex.org/W1917718277","https://openalex.org/W1964127768","https://openalex.org/W1969747427","https://openalex.org/W1979348184","https://openalex.org/W1992699367","https://openalex.org/W1994623790","https://openalex.org/W1995903777","https://openalex.org/W1997537631","https://openalex.org/W2008499636","https://openalex.org/W2013577806","https://openalex.org/W2033668463","https://openalex.org/W2041728612","https://openalex.org/W2041868356","https://openalex.org/W2044018446","https://openalex.org/W2048083981","https://openalex.org/W2052524720","https://openalex.org/W2056510881","https://openalex.org/W2062520372","https://openalex.org/W2101269255","https://openalex.org/W2102625004","https://openalex.org/W2104433781","https://openalex.org/W2118143383","https://openalex.org/W2118572719","https://openalex.org/W2163197466","https://openalex.org/W2163694708","https://openalex.org/W2611684114","https://openalex.org/W4232401394"],"related_works":["https://openalex.org/W2486460843","https://openalex.org/W2168109476","https://openalex.org/W1968121071","https://openalex.org/W2061647633","https://openalex.org/W4379231730","https://openalex.org/W2020254986","https://openalex.org/W2686985752","https://openalex.org/W1992540108","https://openalex.org/W4389858081","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Motion":[0,57],"segmentation":[1,58],"is":[2,39,59],"an":[3,19],"important":[4],"task":[5],"in":[6,10,24,36,74,123],"video":[7,33,50],"surveillance":[8,32],"and":[9,96,98,110,126],"many":[11],"high":[12],"level":[13],"vision":[14,112],"applications.":[15],"In":[16],"this":[17],"paper,":[18],"adaptive":[20],"method":[21,43,86],"using":[22,51],"statistics":[23],"temporal":[25,77],"framework":[26],"to":[27,115],"segment":[28],"moving":[29],"objects":[30],"from":[31],"sequences":[34],"captured":[35],"dynamic":[37,124],"environment":[38,125],"proposed.":[40],"The":[41],"proposed":[42,121],"first":[44],"preprocesses":[45],"the":[46,92,117,120],"input":[47],"frames":[48],"of":[49,71,119],"Gaussian":[52],"filter":[53],"for":[54],"noise":[55],"reduction.":[56],"done":[60],"by":[61],"employing":[62],"statistical":[63],"T-test":[64],"on":[65,91],"neighborhood":[66],"RGB":[67],"color":[68],"intensity":[69],"values":[70],"each":[72],"pixel":[73],"two":[75],"successive":[76],"frames.":[78],"Several":[79],"experiments":[80],"along":[81],"with":[82,84],"comparison":[83],"existing":[85],"have":[87],"been":[88],"carried":[89],"out":[90],"IEEE":[93,99],"PETS":[94],"(2009":[95],"2013)":[97],"Change":[100],"Detection":[101],"(2014)":[102],"datasets":[103],"which":[104],"include":[105],"thermal,":[106],"normal,":[107],"PTZ,":[108],"aerial":[109],"night":[111],"sensor":[113],"videos":[114],"demonstrate":[116],"efficacy":[118],"methods":[122],"results":[127],"obtained":[128],"are":[129],"encouraging.":[130]},"counts_by_year":[{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}