{"id":"https://openalex.org/W4402595396","doi":"https://doi.org/10.1109/avss61716.2024.10672588","title":"PedRiskNet: Classifying Pedestrian Situations in Surveillance Videos for Pedestrian Safety Monitoring in Smart Cities","display_name":"PedRiskNet: Classifying Pedestrian Situations in Surveillance Videos for Pedestrian Safety Monitoring in Smart Cities","publication_year":2024,"publication_date":"2024-07-15","ids":{"openalex":"https://openalex.org/W4402595396","doi":"https://doi.org/10.1109/avss61716.2024.10672588"},"language":"en","primary_location":{"id":"doi:10.1109/avss61716.2024.10672588","is_oa":false,"landing_page_url":"https://doi.org/10.1109/avss61716.2024.10672588","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)","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/A5055987476","display_name":"Dae Hoe Kim","orcid":null},"institutions":[{"id":"https://openalex.org/I142401562","display_name":"Electronics and Telecommunications Research Institute","ror":"https://ror.org/03ysstz10","country_code":"KR","type":"facility","lineage":["https://openalex.org/I142401562","https://openalex.org/I2801339556","https://openalex.org/I4210144908","https://openalex.org/I4387152098"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Dae Hoe Kim","raw_affiliation_strings":["Electronics and Telecommunications Research Institute (ETRI),South Korea"],"affiliations":[{"raw_affiliation_string":"Electronics and Telecommunications Research Institute (ETRI),South Korea","institution_ids":["https://openalex.org/I142401562"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101852466","display_name":"Jinyoung Moon","orcid":"https://orcid.org/0009-0003-5314-0605"},"institutions":[{"id":"https://openalex.org/I142401562","display_name":"Electronics and Telecommunications Research Institute","ror":"https://ror.org/03ysstz10","country_code":"KR","type":"facility","lineage":["https://openalex.org/I142401562","https://openalex.org/I2801339556","https://openalex.org/I4210144908","https://openalex.org/I4387152098"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jinyoung Moon","raw_affiliation_strings":["Electronics and Telecommunications Research Institute (ETRI),South Korea"],"affiliations":[{"raw_affiliation_string":"Electronics and Telecommunications Research Institute (ETRI),South Korea","institution_ids":["https://openalex.org/I142401562"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5055987476"],"corresponding_institution_ids":["https://openalex.org/I142401562"],"apc_list":null,"apc_paid":null,"fwci":1.4812,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.80560261,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9797000288963318,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9797000288963318,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9369000196456909,"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.916700005531311,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.9054644703865051},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6772871017456055},{"id":"https://openalex.org/keywords/pedestrian-detection","display_name":"Pedestrian detection","score":0.6647294759750366},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4029672145843506},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.3793763518333435},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.29181426763534546},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.19306522607803345}],"concepts":[{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.9054644703865051},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6772871017456055},{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.6647294759750366},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4029672145843506},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.3793763518333435},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.29181426763534546},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.19306522607803345}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/avss61716.2024.10672588","is_oa":false,"landing_page_url":"https://doi.org/10.1109/avss61716.2024.10672588","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.699999988079071}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1861492603","https://openalex.org/W2076881576","https://openalex.org/W2107775979","https://openalex.org/W2150066425","https://openalex.org/W2165880761","https://openalex.org/W2594507094","https://openalex.org/W2781228439","https://openalex.org/W2795817893","https://openalex.org/W3034971973","https://openalex.org/W3042011474","https://openalex.org/W3082590664","https://openalex.org/W3110317294","https://openalex.org/W4206580383","https://openalex.org/W4206956855","https://openalex.org/W4206988772","https://openalex.org/W4224980671","https://openalex.org/W4286904999","https://openalex.org/W4309995559","https://openalex.org/W4312815172","https://openalex.org/W4320736147","https://openalex.org/W4385245566","https://openalex.org/W4385805055","https://openalex.org/W6620707391","https://openalex.org/W6637373629","https://openalex.org/W6696085341","https://openalex.org/W6757817989","https://openalex.org/W6776598532","https://openalex.org/W6947681574"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2392100589","https://openalex.org/W2512789322","https://openalex.org/W2101960027","https://openalex.org/W2197846993","https://openalex.org/W49697837","https://openalex.org/W2586575957","https://openalex.org/W2972620127","https://openalex.org/W2981141433"],"abstract_inverted_index":{"In":[0],"the":[1,39,95],"context":[2,41],"of":[3,42,45,105],"smart":[4,135],"cities,":[5,136],"pedestrian":[6,16,25,51,61,106,132],"safety":[7,133],"enhancement":[8],"through":[9],"visual":[10],"AI-based":[11],"technology":[12],"is":[13],"crucial.":[14],"While":[15],"detection":[17],"and":[18,69,76,98,140,145],"tracking":[19],"have":[20],"been":[21],"extensively":[22],"studied,":[23],"classifying":[24],"situations":[26,44],"for":[27,102,130],"immediate":[28],"risk":[29],"assessment":[30],"remains":[31],"challenging.":[32],"Existing":[33],"methods":[34],"often":[35],"fail":[36],"to":[37,84,122,142],"consider":[38],"broader":[40],"unsafe":[43],"pedestrians":[46],"or":[47],"rely":[48],"solely":[49],"on":[50,110],"detection.":[52],"To":[53],"address":[54],"this":[55],"gap,":[56],"we":[57,79],"propose":[58],"a":[59,111],"novel":[60],"situation":[62],"classification":[63,104],"method":[64,90],"incorporating":[65],"ground":[66,81,99],"region":[67,82],"estimation":[68],"multi-modal":[70,92],"fusion.":[71],"By":[72],"utilizing":[73],"semantic":[74],"segmentation":[75],"temporal":[77],"consistency,":[78],"estimate":[80],"maps":[83],"mitigate":[85,143],"occlusion":[86],"effects.":[87],"The":[88],"proposed":[89],"fuses":[91],"features":[93],"from":[94],"local":[96],"surroundings":[97],"regions,":[100],"allowing":[101],"accurate":[103],"situations.":[107],"Experimental":[108],"results":[109],"public":[112],"dataset":[113],"recorded":[114],"in":[115,134],"school":[116],"zones":[117],"demonstrate":[118],"superior":[119],"performance":[120],"compared":[121],"baseline":[123],"models.":[124],"This":[125],"approach":[126],"holds":[127],"significant":[128],"potential":[129],"improving":[131],"enabling":[137],"proactive":[138],"measures":[139],"interventions":[141],"risks":[144],"enhance":[146],"overall":[147],"road":[148],"safety.":[149]},"counts_by_year":[{"year":2025,"cited_by_count":5}],"updated_date":"2025-12-23T23:11:35.936235","created_date":"2025-10-10T00:00:00"}
