{"id":"https://openalex.org/W2028629089","doi":"https://doi.org/10.1109/ispa.2013.6703744","title":"Sparse coding and Gaussian modeling of coefficients average for background subtraction","display_name":"Sparse coding and Gaussian modeling of coefficients average for background subtraction","publication_year":2013,"publication_date":"2013-09-01","ids":{"openalex":"https://openalex.org/W2028629089","doi":"https://doi.org/10.1109/ispa.2013.6703744","mag":"2028629089"},"language":"en","primary_location":{"id":"doi:10.1109/ispa.2013.6703744","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ispa.2013.6703744","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 8th International Symposium on Image and Signal Processing and Analysis (ISPA)","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/A5102291082","display_name":"Ciprian David","orcid":null},"institutions":[{"id":"https://openalex.org/I3122695212","display_name":"Polytechnic University of Timi\u015foara","ror":"https://ror.org/02v91gy68","country_code":"RO","type":"education","lineage":["https://openalex.org/I3122695212"]}],"countries":["RO"],"is_corresponding":true,"raw_author_name":"Ciprian David","raw_affiliation_strings":["Communications Department, \u201cPolitehnica\u201d University of Timisoara, Timisoara, Romania","Commun. Dept., \u201cPoliteh.\u201d Univ. of Timisoara, Timisoara, Romania"],"affiliations":[{"raw_affiliation_string":"Communications Department, \u201cPolitehnica\u201d University of Timisoara, Timisoara, Romania","institution_ids":["https://openalex.org/I3122695212"]},{"raw_affiliation_string":"Commun. Dept., \u201cPoliteh.\u201d Univ. of Timisoara, Timisoara, Romania","institution_ids":["https://openalex.org/I3122695212"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006901264","display_name":"Vasile Gui","orcid":null},"institutions":[{"id":"https://openalex.org/I3122695212","display_name":"Polytechnic University of Timi\u015foara","ror":"https://ror.org/02v91gy68","country_code":"RO","type":"education","lineage":["https://openalex.org/I3122695212"]}],"countries":["RO"],"is_corresponding":false,"raw_author_name":"Vasile Gui","raw_affiliation_strings":["Communications Department, \u201cPolitehnica\u201d University of Timisoara, Timisoara, Romania","Commun. Dept., \u201cPoliteh.\u201d Univ. of Timisoara, Timisoara, Romania"],"affiliations":[{"raw_affiliation_string":"Communications Department, \u201cPolitehnica\u201d University of Timisoara, Timisoara, Romania","institution_ids":["https://openalex.org/I3122695212"]},{"raw_affiliation_string":"Commun. Dept., \u201cPoliteh.\u201d Univ. of Timisoara, Timisoara, Romania","institution_ids":["https://openalex.org/I3122695212"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5102291082"],"corresponding_institution_ids":["https://openalex.org/I3122695212"],"apc_list":null,"apc_paid":null,"fwci":1.3608,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.83465788,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"230","last_page":"235"},"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9987999796867371,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9968000054359436,"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/background-subtraction","display_name":"Background subtraction","score":0.781569242477417},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.60587078332901},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5802619457244873},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5473194718360901},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5282068848609924},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.52601557970047},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.4940634071826935},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.4624502956867218},{"id":"https://openalex.org/keywords/subtraction","display_name":"Subtraction","score":0.4620048701763153},{"id":"https://openalex.org/keywords/neural-coding","display_name":"Neural coding","score":0.45393526554107666},{"id":"https://openalex.org/keywords/foreground-detection","display_name":"Foreground detection","score":0.43840479850769043},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.39332038164138794},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.35965490341186523},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.25287237763404846}],"concepts":[{"id":"https://openalex.org/C32653426","wikidata":"https://www.wikidata.org/wiki/Q3813641","display_name":"Background subtraction","level":3,"score":0.781569242477417},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.60587078332901},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5802619457244873},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5473194718360901},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5282068848609924},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.52601557970047},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.4940634071826935},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.4624502956867218},{"id":"https://openalex.org/C68060419","wikidata":"https://www.wikidata.org/wiki/Q40754","display_name":"Subtraction","level":2,"score":0.4620048701763153},{"id":"https://openalex.org/C77637269","wikidata":"https://www.wikidata.org/wiki/Q7002051","display_name":"Neural coding","level":2,"score":0.45393526554107666},{"id":"https://openalex.org/C2779769447","wikidata":"https://www.wikidata.org/wiki/Q3813641","display_name":"Foreground detection","level":4,"score":0.43840479850769043},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.39332038164138794},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.35965490341186523},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.25287237763404846},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"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/ispa.2013.6703744","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ispa.2013.6703744","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 8th International Symposium on Image and Signal Processing and Analysis (ISPA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.5199999809265137},{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.44999998807907104}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1499877760","https://openalex.org/W1569600562","https://openalex.org/W1986931325","https://openalex.org/W1991848923","https://openalex.org/W2035866593","https://openalex.org/W2078204800","https://openalex.org/W2110110767","https://openalex.org/W2111918405","https://openalex.org/W2113577207","https://openalex.org/W2127070222","https://openalex.org/W2129812935","https://openalex.org/W2135046866","https://openalex.org/W2140235142","https://openalex.org/W2143373691","https://openalex.org/W2158604775","https://openalex.org/W2166978545","https://openalex.org/W2316304551","https://openalex.org/W2734906113","https://openalex.org/W4231795354","https://openalex.org/W6629695367","https://openalex.org/W6740834477"],"related_works":["https://openalex.org/W2105103921","https://openalex.org/W2028059897","https://openalex.org/W2086414697","https://openalex.org/W2012314832","https://openalex.org/W2953123162","https://openalex.org/W2188430267","https://openalex.org/W4298195641","https://openalex.org/W2110416663","https://openalex.org/W3010714307","https://openalex.org/W1484372434"],"abstract_inverted_index":{"A":[0,85,102,134],"sparse":[1,38],"coding":[2],"based":[3],"approach":[4,41,145],"for":[5],"background":[6,14],"subtraction":[7],"is":[8,16,52,83,146,152],"proposed":[9],"in":[10,158],"this":[11,91],"paper.":[12],"The":[13,46],"model":[15,75],"composed":[17],"from":[18,90],"a":[19,23,43,50],"K-SVD":[20],"dictionary":[21],"and":[22,130,163],"set":[24,82],"of":[25,37,49,79,160],"mean":[26],"coefficients":[27,81],"associated":[28],"to":[29,34,62,154],"each":[30],"image":[31,58,88,108],"location.":[32],"Due":[33],"the":[35,56,77,80,97,106,118,123,127,131,141],"use":[36],"coding,":[39],"our":[40],"has":[42],"regional":[44],"character.":[45],"recovered":[47],"value":[48],"pixel":[51],"obtained":[53],"by":[54,66,122],"reconstructing":[55],"surrounding":[57],"patch.":[59],"In":[60],"order":[61],"avoid":[63],"problems":[64],"introduced":[65],"difficult":[67],"situations":[68],"like":[69],"dynamic":[70],"backgrounds,":[71],"an":[72],"additional":[73],"Gaussian":[74],"on":[76,105,137],"average":[78],"used.":[84],"foreground":[86,111],"confidence":[87,107],"results":[89],"modeling.":[92],"Two":[93],"threshold":[94,104,136],"will":[95],"output":[96],"final":[98,142],"background-foreground":[99],"binary":[100],"map.":[101],"first":[103],"selects":[109],"possible":[110],"candidates.":[112],"For":[113],"these":[114,138],"candidates":[115,139],"we":[116],"consider":[117],"reconstruction":[119],"error,":[120],"represented":[121],"absolute":[124],"difference":[125],"between":[126],"reconstructed":[128],"frame":[129],"estimated":[132],"background.":[133],"second":[135],"offers":[140],"discrimination.":[143],"Our":[144],"tested":[147],"against":[148],"state-of-the-art":[149],"methods.":[150],"It":[151],"proved":[153],"perform":[155],"better":[156],"both":[157],"terms":[159],"visual":[161],"comparison":[162],"quantitative":[164],"measures.":[165]},"counts_by_year":[{"year":2019,"cited_by_count":2},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":2},{"year":2013,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}