{"id":"https://openalex.org/W2899753566","doi":"https://doi.org/10.1109/access.2018.2879156","title":"Structural Regression Model Based Inverse Sparse Representation for Tracking Objects","display_name":"Structural Regression Model Based Inverse Sparse Representation for Tracking Objects","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2899753566","doi":"https://doi.org/10.1109/access.2018.2879156","mag":"2899753566"},"language":"en","primary_location":{"id":"doi:10.1109/access.2018.2879156","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2879156","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2018.2879156","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100736324","display_name":"Xiaowei An","orcid":"https://orcid.org/0000-0002-8672-5728"},"institutions":[{"id":"https://openalex.org/I80143920","display_name":"Shandong University of Science and Technology","ror":"https://ror.org/04gtjhw98","country_code":"CN","type":"education","lineage":["https://openalex.org/I80143920"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaowei An","raw_affiliation_strings":["College of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao, China"],"raw_orcid":"https://orcid.org/0000-0002-8672-5728","affiliations":[{"raw_affiliation_string":"College of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao, China","institution_ids":["https://openalex.org/I80143920"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101879798","display_name":"Nongliang Sun","orcid":"https://orcid.org/0000-0002-5317-8924"},"institutions":[{"id":"https://openalex.org/I80143920","display_name":"Shandong University of Science and Technology","ror":"https://ror.org/04gtjhw98","country_code":"CN","type":"education","lineage":["https://openalex.org/I80143920"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Nongliang Sun","raw_affiliation_strings":["College of Electronics, Communication and Physics, Shandong University of Science and Technology, Qingdao, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electronics, Communication and Physics, Shandong University of Science and Technology, Qingdao, China","institution_ids":["https://openalex.org/I80143920"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103237302","display_name":"Maoyong Cao","orcid":"https://orcid.org/0000-0003-4135-1512"},"institutions":[{"id":"https://openalex.org/I80143920","display_name":"Shandong University of Science and Technology","ror":"https://ror.org/04gtjhw98","country_code":"CN","type":"education","lineage":["https://openalex.org/I80143920"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Maoyong Cao","raw_affiliation_strings":["College of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao, China"],"raw_orcid":"https://orcid.org/0000-0003-4135-1512","affiliations":[{"raw_affiliation_string":"College of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao, China","institution_ids":["https://openalex.org/I80143920"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I80143920"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.5202,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.71515967,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"6","issue":null,"first_page":"69978","last_page":"69987"},"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9865000247955322,"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"}},{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.9745000004768372,"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/robustness","display_name":"Robustness (evolution)","score":0.6862727403640747},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6521260738372803},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.6309531927108765},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.541368842124939},{"id":"https://openalex.org/keywords/partial-least-squares-regression","display_name":"Partial least squares regression","score":0.5363672375679016},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5321919918060303},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.492692768573761},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.47813355922698975},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4513565003871918},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4426960349082947},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4260198175907135},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3404950499534607},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2957451343536377},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.20590460300445557}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6862727403640747},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6521260738372803},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.6309531927108765},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.541368842124939},{"id":"https://openalex.org/C22354355","wikidata":"https://www.wikidata.org/wiki/Q422009","display_name":"Partial least squares regression","level":2,"score":0.5363672375679016},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5321919918060303},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.492692768573761},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.47813355922698975},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4513565003871918},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4426960349082947},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4260198175907135},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3404950499534607},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2957451343536377},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.20590460300445557},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2018.2879156","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2879156","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:26e9309d599c4fd7862f53a147efc60b","is_oa":false,"landing_page_url":"https://doaj.org/article/26e9309d599c4fd7862f53a147efc60b","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 6, Pp 69978-69987 (2018)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2018.2879156","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2879156","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G256171925","display_name":null,"funder_award_id":"61801270","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322522","display_name":"Shandong University of Science and Technology","ror":"https://ror.org/04gtjhw98"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W73598692","https://openalex.org/W988466463","https://openalex.org/W1566135517","https://openalex.org/W1991727946","https://openalex.org/W1995903777","https://openalex.org/W1999788504","https://openalex.org/W2001785244","https://openalex.org/W2003060733","https://openalex.org/W2008732654","https://openalex.org/W2016075127","https://openalex.org/W2029683515","https://openalex.org/W2066513304","https://openalex.org/W2089961441","https://openalex.org/W2121317779","https://openalex.org/W2124211486","https://openalex.org/W2137225583","https://openalex.org/W2139047213","https://openalex.org/W2158917775","https://openalex.org/W2162383208","https://openalex.org/W2167089254","https://openalex.org/W2183648259","https://openalex.org/W2211629196","https://openalex.org/W2280226538","https://openalex.org/W2429528072","https://openalex.org/W2596079526","https://openalex.org/W4206310440","https://openalex.org/W4207002640","https://openalex.org/W6625882733","https://openalex.org/W6678488983","https://openalex.org/W6680302564","https://openalex.org/W6683636472","https://openalex.org/W6683886257"],"related_works":["https://openalex.org/W2429686810","https://openalex.org/W2371059786","https://openalex.org/W2407375987","https://openalex.org/W3049691116","https://openalex.org/W2505726097","https://openalex.org/W2950975704","https://openalex.org/W2010643158","https://openalex.org/W2106867672","https://openalex.org/W4310268968","https://openalex.org/W4297815943"],"abstract_inverted_index":{"In":[0,125],"order":[1],"to":[2,87,106,121,133,145],"reduce":[3],"the":[4,9,75,82,89,93,108,113,127,159],"calculation":[5],"cost":[6],"and":[7,29,67,100,137],"improve":[8],"robustness":[10],"of":[11,24,117],"appearance":[12,69,119,123],"model,":[13],"this":[14],"paper":[15],"presents":[16],"an":[17],"optimal":[18],"object":[19],"tracking":[20,62,76,161],"method":[21],"that":[22,158],"consists":[23],"improved":[25],"inverse":[26,94],"sparse":[27,95],"representation":[28,96],"global":[30],"spatial":[31,79],"envelope.":[32],"First,":[33],"partial":[34,65],"least":[35],"squares":[36],"regression-based":[37],"structural":[38,115],"model":[39,140],"is":[40,85,131,143],"adopted,":[41],"which":[42,111],"easily":[43,58],"facilitates":[44],"target":[45],"template":[46],"sparsely":[47],"represented":[48],"by":[49,149],"candidate":[50,91,135],"dictionary.":[51],"Furthermore,":[52],"candidates":[53],"with":[54],"nonzero":[55],"coefficients":[56],"are":[57,71,104],"selected":[59],"as":[60],"possible":[61],"results.":[63],"Meanwhile,":[64],"occlusion":[66],"slight":[68],"changes":[70],"effectively":[72],"alleviated":[73],"during":[74],"process.":[77,97],"Second,":[78],"envelope":[80],"in":[81,167],"frequency":[83],"domain":[84],"utilized":[86],"select":[88],"best":[90],"from":[92],"Multiple":[98],"scales":[99],"orientations-based":[101],"Gabor":[102],"filters":[103],"established":[105],"obtain":[107],"Gist":[109],"information,":[110],"keeps":[112],"potential":[114],"attributes":[116],"local":[118],"models":[120],"tolerate":[122],"variation.":[124],"addition,":[126],"Bayesian":[128],"inference":[129],"framework":[130],"used":[132],"exploit":[134],"samples,":[136],"a":[138,164],"simple":[139],"update":[141],"scheme":[142],"employed":[144],"alleviate":[146],"drifting":[147],"caused":[148],"temporal":[150],"varying":[151],"multi-factors.":[152],"The":[153],"qualitative":[154],"experimental":[155],"results":[156],"show":[157],"proposed":[160],"algorithm":[162],"provides":[163],"better":[165],"performance":[166],"some":[168],"dynamic":[169],"scenes.":[170]},"counts_by_year":[{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}