{"id":"https://openalex.org/W1539787149","doi":"https://doi.org/10.1109/ascc.2015.7244586","title":"Vision-based traffic accident detection using matrix approximation","display_name":"Vision-based traffic accident detection using matrix approximation","publication_year":2015,"publication_date":"2015-05-01","ids":{"openalex":"https://openalex.org/W1539787149","doi":"https://doi.org/10.1109/ascc.2015.7244586","mag":"1539787149"},"language":"en","primary_location":{"id":"doi:10.1109/ascc.2015.7244586","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ascc.2015.7244586","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 10th Asian Control Conference (ASCC)","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/A5021020582","display_name":"Siyu Xia","orcid":null},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Siyu Xia","raw_affiliation_strings":["Ministry of Education, School of Automation Southeast University, Nanjing, China","Key Laboratory of Measurement and Control of CSE, Ministry of Education, School of Automation Southeast University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Ministry of Education, School of Automation Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"Key Laboratory of Measurement and Control of CSE, Ministry of Education, School of Automation Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101686186","display_name":"Xiong Jian","orcid":"https://orcid.org/0000-0002-6005-0398"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Xiong","raw_affiliation_strings":["Ministry of Education, School of Automation Southeast University, Nanjing, China","Key Laboratory of Measurement and Control of CSE, Ministry of Education, School of Automation Southeast University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Ministry of Education, School of Automation Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"Key Laboratory of Measurement and Control of CSE, Ministry of Education, School of Automation Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100761763","display_name":"Ying Liu","orcid":"https://orcid.org/0000-0002-9037-7818"},"institutions":[{"id":"https://openalex.org/I4210151926","display_name":"Hengyang Academy of Agricultural Sciences","ror":"https://ror.org/04dtbmg64","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210151926"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ying Liu","raw_affiliation_strings":["Hengyang Experimental Middle School, Hengyang, China"],"affiliations":[{"raw_affiliation_string":"Hengyang Experimental Middle School, Hengyang, China","institution_ids":["https://openalex.org/I4210151926"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085757311","display_name":"Gang Li","orcid":"https://orcid.org/0000-0002-4195-6899"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gang Li","raw_affiliation_strings":["Nanjing Sample Technology Group Co., Ltd., Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Nanjing Sample Technology Group Co., Ltd., Nanjing, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5021020582"],"corresponding_institution_ids":["https://openalex.org/I76569877"],"apc_list":null,"apc_paid":null,"fwci":0.7364,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.77809789,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9991999864578247,"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":0.9991999864578247,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9980999827384949,"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"}},{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9952999949455261,"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/computer-science","display_name":"Computer science","score":0.761323869228363},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6631582379341125},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6541011333465576},{"id":"https://openalex.org/keywords/low-rank-approximation","display_name":"Low-rank approximation","score":0.5881175398826599},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.4798135757446289},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4620586633682251},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.45721033215522766},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.45521754026412964},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4461266100406647},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.43963080644607544},{"id":"https://openalex.org/keywords/linear-subspace","display_name":"Linear subspace","score":0.4361845850944519},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4336315095424652},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.4254269003868103},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1411532759666443},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09109172224998474},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.08400008082389832},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.07677221298217773}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.761323869228363},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6631582379341125},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6541011333465576},{"id":"https://openalex.org/C90199385","wikidata":"https://www.wikidata.org/wiki/Q6692777","display_name":"Low-rank approximation","level":3,"score":0.5881175398826599},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.4798135757446289},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4620586633682251},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.45721033215522766},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.45521754026412964},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4461266100406647},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.43963080644607544},{"id":"https://openalex.org/C12362212","wikidata":"https://www.wikidata.org/wiki/Q728435","display_name":"Linear subspace","level":2,"score":0.4361845850944519},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4336315095424652},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.4254269003868103},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1411532759666443},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09109172224998474},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.08400008082389832},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.07677221298217773},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C25023664","wikidata":"https://www.wikidata.org/wiki/Q1575637","display_name":"Hankel matrix","level":2,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ascc.2015.7244586","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ascc.2015.7244586","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 10th Asian Control Conference (ASCC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.8299999833106995,"id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1999935624","https://openalex.org/W2091845730","https://openalex.org/W2094665250","https://openalex.org/W2099195694","https://openalex.org/W2118877769","https://openalex.org/W2125105611","https://openalex.org/W2131550388","https://openalex.org/W2143646243","https://openalex.org/W2145496892","https://openalex.org/W2147350962","https://openalex.org/W2150263714","https://openalex.org/W2159526734","https://openalex.org/W2165346010","https://openalex.org/W2166802655","https://openalex.org/W3083538725"],"related_works":["https://openalex.org/W2391321755","https://openalex.org/W2949110394","https://openalex.org/W2896134808","https://openalex.org/W4289378085","https://openalex.org/W2071055957","https://openalex.org/W3144354057","https://openalex.org/W4385556248","https://openalex.org/W3213035342","https://openalex.org/W4301870758","https://openalex.org/W3213049004"],"abstract_inverted_index":{"Vision-based":[0],"traffic":[1,9,25,45,106,116],"accident":[2,26,117],"detection":[3],"is":[4,33,66,95],"a":[5,17,28,54,92,109],"significant":[6],"task":[7],"in":[8,27,84],"video":[10,93],"surveillance.":[11],"In":[12],"this":[13],"paper,":[14],"we":[15,114],"propose":[16],"fast":[18],"and":[19,52],"effective":[20],"approach":[21],"to":[22,34,103],"automatically":[23],"detect":[24],"video.":[29],"The":[30,88],"key":[31],"idea":[32],"utilize":[35],"low-rank":[36,100],"matrix":[37,90,101],"approximation":[38,102,125],"based":[39,76],"method.":[40,139],"A":[41],"critical":[42],"observation":[43],"that":[44],"accidents":[46],"usually":[47],"occur":[48],"on":[49,77,129],"road":[50],"area":[51],"occupy":[53],"small":[55],"part":[56],"of":[57,82,91,111,121,124,136],"image":[58],"enlightens":[59],"us":[60],"the":[61,78,85,119,122,134],"following":[62],"research.":[63],"Each":[64],"frame":[65],"first":[67],"divided":[68],"into":[69],"non-overlapping":[70],"blocks":[71,83],"associated":[72],"with":[73,108],"different":[74],"weights":[75],"average":[79],"velocity":[80],"magnitude":[81],"training":[86],"time.":[87],"motion":[89,112],"segmentation":[94],"then":[96],"extracted.":[97],"After":[98],"using":[99],"associate":[104],"normal":[105],"scenes":[107],"set":[110],"subspaces,":[113],"identify":[115],"at":[118],"moment":[120],"increase":[123],"error.":[126],"Experimental":[127],"results":[128],"several":[130],"surveillance":[131],"videos":[132],"demonstrate":[133],"effectiveness":[135],"our":[137],"proposed":[138]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}