{"id":"https://openalex.org/W4392255619","doi":"https://doi.org/10.1145/3633637.3633673","title":"Real-time Sidewalk Anomaly Detection from Surveillance Video with A Combination Model","display_name":"Real-time Sidewalk Anomaly Detection from Surveillance Video with A Combination Model","publication_year":2023,"publication_date":"2023-10-27","ids":{"openalex":"https://openalex.org/W4392255619","doi":"https://doi.org/10.1145/3633637.3633673"},"language":"en","primary_location":{"id":"doi:10.1145/3633637.3633673","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3633637.3633673","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 12th International Conference on Computing and Pattern Recognition","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/A5034573487","display_name":"Yuwen Deng","orcid":"https://orcid.org/0009-0000-0499-6376"},"institutions":[{"id":"https://openalex.org/I75867142","display_name":"Xiamen University of Technology","ror":"https://ror.org/01285e189","country_code":"CN","type":"education","lineage":["https://openalex.org/I75867142"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuwen Deng","raw_affiliation_strings":["College of Computer and Information Engineering, Xiamen University of Technology, China"],"affiliations":[{"raw_affiliation_string":"College of Computer and Information Engineering, Xiamen University of Technology, China","institution_ids":["https://openalex.org/I75867142"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100352673","display_name":"Feng Chen","orcid":"https://orcid.org/0000-0001-7849-2023"},"institutions":[{"id":"https://openalex.org/I75867142","display_name":"Xiamen University of Technology","ror":"https://ror.org/01285e189","country_code":"CN","type":"education","lineage":["https://openalex.org/I75867142"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Chen","raw_affiliation_strings":["College of Computer and Information Engineering, Xiamen University of Technology, China"],"affiliations":[{"raw_affiliation_string":"College of Computer and Information Engineering, Xiamen University of Technology, China","institution_ids":["https://openalex.org/I75867142"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5034573487"],"corresponding_institution_ids":["https://openalex.org/I75867142"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.20705612,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"229","last_page":"234"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":1.0,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9973000288009644,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9731000065803528,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/anomaly-detection","display_name":"Anomaly detection","score":0.7711690068244934},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.738427460193634},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6113475561141968},{"id":"https://openalex.org/keywords/dilation","display_name":"Dilation (metric space)","score":0.5984888672828674},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5557547807693481},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5509150624275208},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.5343135595321655},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.5056076049804688},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.45393598079681396},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.43236038088798523},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4322412610054016},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3747500479221344},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3235568702220917}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7711690068244934},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.738427460193634},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6113475561141968},{"id":"https://openalex.org/C2780757906","wikidata":"https://www.wikidata.org/wiki/Q5276676","display_name":"Dilation (metric space)","level":2,"score":0.5984888672828674},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5557547807693481},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5509150624275208},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.5343135595321655},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.5056076049804688},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.45393598079681396},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.43236038088798523},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4322412610054016},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3747500479221344},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3235568702220917},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"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/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C26873012","wikidata":"https://www.wikidata.org/wiki/Q214781","display_name":"Condensed matter physics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3633637.3633673","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3633637.3633673","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 12th International Conference on Computing and Pattern Recognition","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.4699999988079071,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1964806982","https://openalex.org/W1967456674","https://openalex.org/W2164489414","https://openalex.org/W2739846485","https://openalex.org/W2777342313","https://openalex.org/W2777556841","https://openalex.org/W2904013130","https://openalex.org/W2933801392","https://openalex.org/W2960737790","https://openalex.org/W2971931942","https://openalex.org/W2993182889","https://openalex.org/W3035240825","https://openalex.org/W3047032303","https://openalex.org/W6642206748","https://openalex.org/W6750227808"],"related_works":["https://openalex.org/W2806741695","https://openalex.org/W4290647774","https://openalex.org/W3189286258","https://openalex.org/W3207797160","https://openalex.org/W3210364259","https://openalex.org/W4300558037","https://openalex.org/W2667207928","https://openalex.org/W2912112202","https://openalex.org/W4377864969","https://openalex.org/W3120251014"],"abstract_inverted_index":{"Abnormal":[0],"event":[1],"detection":[2,18,152],"is":[3],"a":[4,46,57],"hot":[5],"topic":[6],"in":[7,13,37,51,144],"the":[8,15,26,66,70,94,105,111,128,142,147,155,162],"field":[9],"of":[10,97,110,127,135],"intelligent":[11],"monitoring,":[12],"which":[14,140,161],"sidewalk":[16,43,98,101],"anomaly":[17,44,151],"plays":[19],"an":[20],"important":[21],"role.":[22],"Aiming":[23],"to":[24,32,64,87,168],"solve":[25],"problems":[27],"(e.g.,":[28],"time-consuming,":[29],"laborious,":[30],"easy":[31],"delay,":[33],"omission,":[34],"and":[35,68,81,100,125,150,171],"occlusion)":[36],"surveillance":[38],"video":[39],"processes":[40],"for":[41],"real-time":[42,58,95],"detection,":[45],"combination":[47,156],"model":[48,157],"was":[49,62,85,114,121,131,158],"proposed":[50],"this":[52],"paper.":[53],"Firstly,":[54],"YOLACT++":[55,130],"as":[56],"instance":[59],"segmentation":[60],"algorithm":[61],"used":[63,86],"segment":[65],"sidewalk,":[67,92],"then":[69],"segmented":[71],"results":[72,107],"were":[73,137,166],"post-processed":[74],"through":[75,160],"ordinary":[76],"image":[77],"operations":[78],"(i.e.":[79],"dilation":[80],"erosion).":[82],"Finally,":[83],"YOLOv3":[84,113],"detect":[88],"illegal":[89,102],"vehicles":[90,163],"on":[91],"realizing":[93],"monitoring":[96],"parking":[99],"driving.":[103],"As":[104],"experiments":[106],"showed,":[108],"accuracy":[109],"trained":[112,129],"greater":[115],"than":[116],"80%":[117],"when":[118],"IOU":[119],"threshold":[120],"set":[122],"at":[123],"0.5,":[124],"mAP":[126],"0.45.":[132],"The":[133],"FPSs":[134],"them":[136],"above":[138],"30,":[139],"meet":[141],"requirements":[143],"practice.":[145],"On":[146],"activity":[148],"modeling":[149],"data":[153],"set,":[154],"tested,":[159],"invading":[164],"sidewalks":[165],"able":[167],"be":[169],"quickly":[170],"accurately":[172],"identified.":[173]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}