{"id":"https://openalex.org/W4281779438","doi":"https://doi.org/10.1109/ipta54936.2022.9784118","title":"Towards Fast and Accurate Intimate Contact Recognition through Video Analysis","display_name":"Towards Fast and Accurate Intimate Contact Recognition through Video Analysis","publication_year":2022,"publication_date":"2022-04-19","ids":{"openalex":"https://openalex.org/W4281779438","doi":"https://doi.org/10.1109/ipta54936.2022.9784118"},"language":"en","primary_location":{"id":"doi:10.1109/ipta54936.2022.9784118","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ipta54936.2022.9784118","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 Eleventh International Conference on Image Processing Theory, Tools and Applications (IPTA)","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/A5100552550","display_name":"Yuhao Luo","orcid":"https://orcid.org/0000-0001-5182-6783"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuhao Luo","raw_affiliation_strings":["School of Computer Science and Engineering, University of Electronic Science and Technology of China,Chengdu,China","School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, University of Electronic Science and Technology of China,Chengdu,China","institution_ids":["https://openalex.org/I150229711"]},{"raw_affiliation_string":"School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044892883","display_name":"Hengjing Zhang","orcid":"https://orcid.org/0000-0003-3968-3059"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hengjing Zhang","raw_affiliation_strings":["School of Software Engineering, University of Science and Technology of China,Hefei,China","School of Software Engineering, University of Science and Technology of China, Hefei, China"],"affiliations":[{"raw_affiliation_string":"School of Software Engineering, University of Science and Technology of China,Hefei,China","institution_ids":["https://openalex.org/I126520041"]},{"raw_affiliation_string":"School of Software Engineering, University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076290816","display_name":"Hengchang Liu","orcid":"https://orcid.org/0000-0002-9006-0546"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hengchang Liu","raw_affiliation_strings":["School of Computer Science and Engineering, University of Electronic Science and Technology of China,Chengdu,China","School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, University of Electronic Science and Technology of China,Chengdu,China","institution_ids":["https://openalex.org/I150229711"]},{"raw_affiliation_string":"School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100552550"],"corresponding_institution_ids":["https://openalex.org/I150229711"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.04351634,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9994000196456909,"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":0.9994000196456909,"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":0.9968000054359436,"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/T12943","display_name":"COVID-19 Digital Contact Tracing","score":0.9894000291824341,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/contact-tracing","display_name":"Contact tracing","score":0.7656450271606445},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7548187971115112},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.6268512010574341},{"id":"https://openalex.org/keywords/tracing","display_name":"Tracing","score":0.6027144193649292},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5509122014045715},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.5037314295768738},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4949008822441101},{"id":"https://openalex.org/keywords/identity","display_name":"Identity (music)","score":0.4440375864505768},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4372907280921936},{"id":"https://openalex.org/keywords/coronavirus-disease-2019","display_name":"Coronavirus disease 2019 (COVID-19)","score":0.4369061589241028},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4155319333076477},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09459105134010315}],"concepts":[{"id":"https://openalex.org/C113162765","wikidata":"https://www.wikidata.org/wiki/Q1128437","display_name":"Contact tracing","level":5,"score":0.7656450271606445},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7548187971115112},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.6268512010574341},{"id":"https://openalex.org/C138673069","wikidata":"https://www.wikidata.org/wiki/Q322229","display_name":"Tracing","level":2,"score":0.6027144193649292},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5509122014045715},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.5037314295768738},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4949008822441101},{"id":"https://openalex.org/C2778355321","wikidata":"https://www.wikidata.org/wiki/Q17079427","display_name":"Identity (music)","level":2,"score":0.4440375864505768},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4372907280921936},{"id":"https://openalex.org/C3008058167","wikidata":"https://www.wikidata.org/wiki/Q84263196","display_name":"Coronavirus disease 2019 (COVID-19)","level":4,"score":0.4369061589241028},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4155319333076477},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09459105134010315},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","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/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C524204448","wikidata":"https://www.wikidata.org/wiki/Q788926","display_name":"Infectious disease (medical specialty)","level":3,"score":0.0},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ipta54936.2022.9784118","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ipta54936.2022.9784118","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 Eleventh International Conference on Image Processing Theory, Tools and Applications (IPTA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.75,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W2194775991","https://openalex.org/W2204750386","https://openalex.org/W2520774990","https://openalex.org/W2584637367","https://openalex.org/W2598634450","https://openalex.org/W2787542196","https://openalex.org/W2795758732","https://openalex.org/W2898047322","https://openalex.org/W2946574625","https://openalex.org/W2963842104","https://openalex.org/W2981684125","https://openalex.org/W3026346600","https://openalex.org/W3046908050","https://openalex.org/W3091468319","https://openalex.org/W3100506510","https://openalex.org/W3120048558","https://openalex.org/W3157808808","https://openalex.org/W3160960346","https://openalex.org/W3163371447","https://openalex.org/W3186984225","https://openalex.org/W3203434610","https://openalex.org/W6726946684","https://openalex.org/W6769981643"],"related_works":["https://openalex.org/W4213139346","https://openalex.org/W3204036590","https://openalex.org/W1989717680","https://openalex.org/W3158100496","https://openalex.org/W3130225502","https://openalex.org/W2170160357","https://openalex.org/W4399915950","https://openalex.org/W2012140923","https://openalex.org/W4287554683","https://openalex.org/W2348876715"],"abstract_inverted_index":{"Intimate":[0],"contact":[1,44,66,81,149],"recognition":[2,45],"has":[3],"gained":[4],"more":[5],"attention":[6],"in":[7,10,46,64,76,97,113,140],"academia":[8],"field":[9],"recent":[11],"years":[12],"due":[13],"to":[14,79,143],"the":[15,22,91,114],"outbreak":[16],"of":[17,21,99,111],"Covid-19.":[18],"However,":[19],"state":[20],"art":[23],"solutions":[24],"suffer":[25],"from":[26],"either":[27],"inefficient":[28],"accuracy":[29],"or":[30],"high":[31],"cost.":[32],"In":[33],"this":[34],"paper,":[35],"we":[36],"propose":[37],"a":[38,77],"novel":[39],"method":[40,55],"for":[41],"COVID-19":[42],"intimate":[43],"public":[47,141],"spaces":[48],"through":[49],"video":[50],"camera":[51],"networks":[52],"(CCTV).":[53],"This":[54],"leverages":[56],"distance":[57,87],"detection":[58,88],"and":[59,74,90,122,127,146],"re-Identification":[60],"algorithms,":[61],"so":[62],"pedestrians":[63],"close":[65],"are":[67],"re-identified,":[68],"their":[69],"identity":[70],"information":[71],"is":[72],"obtained":[73],"stored":[75],"database":[78],"realize":[80,144],"tracing.":[82,150],"We":[83,102],"compare":[84],"different":[85],"social":[86],"algorithms":[89],"Faster-RCNN":[92],"model":[93,107],"outperforms":[94],"other":[95],"al-ternatives":[96],"terms":[98],"running":[100],"speed.":[101],"also":[103],"evaluate":[104],"our":[105,134],"Re-Identification":[106],"on":[108],"two":[109],"types":[110],"indicators":[112],"PETS2009":[115],"dataset:":[116],"mAP":[117],"reaches":[118],"85.1%;":[119],"rank-1,":[120],"rank-5,":[121],"rank-10":[123],"reach":[124],"97.8%,":[125],"98.9%,":[126,128],"respectively.":[129],"Experimental":[130],"results":[131],"demonstrate":[132],"that":[133],"solution":[135],"can":[136],"be":[137],"effectively":[138],"applied":[139],"places":[142],"fast":[145],"accurate":[147],"automatic":[148]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}