{"id":"https://openalex.org/W7165668917","doi":"https://doi.org/10.1109/iccect68671.2026.11565269","title":"Research on Cross-Camera Trajectory Prediction Algorithm Based on Big Data Signal Representation and Graph Neural Networks","display_name":"Research on Cross-Camera Trajectory Prediction Algorithm Based on Big Data Signal Representation and Graph Neural Networks","publication_year":2026,"publication_date":"2026-04-28","ids":{"openalex":"https://openalex.org/W7165668917","doi":"https://doi.org/10.1109/iccect68671.2026.11565269"},"language":"en","primary_location":{"id":"doi:10.1109/iccect68671.2026.11565269","doi":"https://doi.org/10.1109/iccect68671.2026.11565269","is_oa":true,"landing_page_url":"https://doi.org/10.1109/iccect68671.2026.11565269","pdf_url":null,"source":{"id":"https://openalex.org/S7407088498","display_name":"IEEE International Conference on Control, Electronics and Computer Technology (ICCECT)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE 4th International Conference on Control, Electronics and Computer Technology (ICCECT)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1109/iccect68671.2026.11565269","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5121548323","display_name":"Xiaoting Yu","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210097448","display_name":"Harbin Huade University","ror":"https://ror.org/00xh1ex65","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210097448"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoting Yu","raw_affiliation_strings":["Harbin Huade University,Harbin,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harbin Huade University,Harbin,China","institution_ids":["https://openalex.org/I4210097448"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100442292","display_name":"Xi Wang","orcid":"https://orcid.org/0000-0003-3910-9575","observed_orcids":["https://orcid.org/0000-0003-3910-9575"]},"institutions":[{"id":"https://openalex.org/I4210097448","display_name":"Harbin Huade University","ror":"https://ror.org/00xh1ex65","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210097448"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xi Wang","raw_affiliation_strings":["Harbin Huade University,Harbin,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harbin Huade University,Harbin,China","institution_ids":["https://openalex.org/I4210097448"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122039166","display_name":"Nannan Jiang","orcid":"https://orcid.org/0009-0009-0270-3758","observed_orcids":["https://orcid.org/0009-0009-0270-3758"]},"institutions":[{"id":"https://openalex.org/I4210097448","display_name":"Harbin Huade University","ror":"https://ror.org/00xh1ex65","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210097448"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Nannan Jiang","raw_affiliation_strings":["Harbin Huade University,Harbin,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harbin Huade University,Harbin,China","institution_ids":["https://openalex.org/I4210097448"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5139162710","display_name":"Xiujuan Li","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210097448","display_name":"Harbin Huade University","ror":"https://ror.org/00xh1ex65","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210097448"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiujuan Li","raw_affiliation_strings":["Harbin Huade University,Harbin,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harbin Huade University,Harbin,China","institution_ids":["https://openalex.org/I4210097448"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210097448"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"556","last_page":"561"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9945999979972839,"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":0.9945999979972839,"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.00139999995008111,"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"}},{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.0012000000569969416,"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/graph-attention-networks","display_name":"graph attention networks","score":0.765999972820282},{"id":"https://openalex.org/keywords/dynamic-graph-topology","display_name":"dynamic graph topology","score":0.7990000247955322},{"id":"https://openalex.org/keywords/multi-camera-video-surveillance","display_name":"multi-camera surveillance","score":0.43299999833106995},{"id":"https://openalex.org/keywords/person-re-identification","display_name":"person re-identification","score":0.7900000214576721},{"id":"https://openalex.org/keywords/occlusion-handling","display_name":"occlusion handling","score":0.7210000157356262},{"id":"https://openalex.org/keywords/intelligent-monitoring","display_name":"intelligent monitoring","score":0.4339999854564667},{"id":"https://openalex.org/keywords/traffic-management","display_name":"traffic management","score":0.7239999771118164}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6449999809265137},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.6284999847412109},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5340999960899353},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5329999923706055},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5322999954223633},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5062999725341797},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.44600000977516174},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4302000105381012},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3580000102519989},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33980000019073486},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.3149000108242035},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.31349998712539673},{"id":"https://openalex.org/C116409475","wikidata":"https://www.wikidata.org/wiki/Q1385056","display_name":"External Data Representation","level":2,"score":0.29109999537467957},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.2858999967575073},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2793999910354614},{"id":"https://openalex.org/C2781170535","wikidata":"https://www.wikidata.org/wiki/Q30587856","display_name":"Noisy data","level":2,"score":0.2768000066280365},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.25540000200271606}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccect68671.2026.11565269","doi":"https://doi.org/10.1109/iccect68671.2026.11565269","is_oa":true,"landing_page_url":"https://doi.org/10.1109/iccect68671.2026.11565269","pdf_url":null,"source":{"id":"https://openalex.org/S7407088498","display_name":"IEEE International Conference on Control, Electronics and Computer Technology (ICCECT)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE 4th International Conference on Control, Electronics and Computer Technology (ICCECT)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1109/iccect68671.2026.11565269","doi":"https://doi.org/10.1109/iccect68671.2026.11565269","is_oa":true,"landing_page_url":"https://doi.org/10.1109/iccect68671.2026.11565269","pdf_url":null,"source":{"id":"https://openalex.org/S7407088498","display_name":"IEEE International Conference on Control, Electronics and Computer Technology (ICCECT)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE 4th International Conference on Control, Electronics and Computer Technology (ICCECT)","raw_type":"proceedings-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":2,"referenced_works":["https://openalex.org/W4414529696","https://openalex.org/W4417484001"],"related_works":["https://openalex.org/W4213236526","https://openalex.org/W7159665094","https://openalex.org/W7167918778","https://openalex.org/W3163616630","https://openalex.org/W7160161510","https://openalex.org/W7203867157","https://openalex.org/W7165618912","https://openalex.org/W7203628711","https://openalex.org/W4408539531","https://openalex.org/W7201855478"],"abstract_inverted_index":{"This":[0,171],"paper":[1],"proposes":[2],"an":[3,24],"Adaptive":[4],"Spatiotemporal":[5],"Signal":[6],"Enhancement":[7],"Graph":[8],"Attention":[9],"Network":[10],"(AST-GAT),":[11],"which":[12,49],"integrates":[13],"big":[14],"data":[15],"signal":[16,43,59,78],"representation":[17],"and":[18,56,67,80,118,122,138,159,167,182,184,194,207],"graph":[19,74,102],"neural":[20],"networks":[21],"to":[22,85,111,129,176],"construct":[23],"integrated":[25],"framework":[26],"of":[27,36,53,90,115],"\u201csignal":[28],"encoding-dynamic":[29],"mapping-spatiotemporal":[30],"prediction,\u201d":[31],"solving":[32],"the":[33,51,58,87,97,135,144],"core":[34],"challenge":[35],"cross-camera":[37,160],"trajectory":[38,156],"prediction.":[39],"An":[40,71],"attention-driven":[41],"heterogeneous":[42],"enhancement":[44],"encoding":[45],"module":[46],"is":[47,83,105,127,149],"designed,":[48],"improves":[50,173],"robustness":[52],"multi-dimensional":[54],"signals":[55],"alleviates":[57],"attenuation":[60],"problem":[61],"across":[62],"cameras":[63],"through":[64],"weight":[65],"allocation":[66],"temporal":[68,109,119],"differential":[69],"enhancement.":[70],"innovative":[72],"dynamic":[73],"topology":[75],"based":[76],"on":[77,134],"similarity":[79],"spatiotemporal":[81],"layout":[82],"used":[84,128],"update":[86],"association":[88,117],"weights":[89,110],"camera":[91],"nodes":[92],"in":[93,188,197],"real":[94],"time,":[95],"replacing":[96],"traditional":[98],"fixed":[99],"topology.":[100],"The":[101],"attention":[103],"mechanism":[104],"improved":[106],"by":[107],"incorporating":[108],"achieve":[112],"collaborative":[113],"modeling":[114],"spatial":[116],"motion":[120],"continuity,":[121],"a":[123],"composite":[124],"loss":[125],"function":[126],"optimize":[130],"model":[131],"training.":[132],"Experiments":[133],"Market-1501,":[136],"DukeMTMC-ReID,":[137],"self-made":[139],"SBHD":[140],"datasets":[141],"validated":[142],"that":[143],"algorithm\u2019s":[145],"average":[146],"positional":[147],"error":[148],"as":[150,152,180,192],"low":[151],"2.3":[153],"pixels,":[154],"with":[155],"prediction":[157],"accuracy":[158],"matching":[161],"success":[162],"rate":[163],"reaching":[164],"$89.7":[165],"\\%$":[166],"$86.3":[168],"\\%$,":[169],"respectively.":[170],"significantly":[172],"performance":[174],"compared":[175],"mainstream":[177],"algorithms":[178],"such":[179,191],"ST-GCN":[181],"ReID+KF,":[183],"demonstrates":[185],"excellent":[186],"adaptability":[187],"complex":[189],"scenarios":[190],"occlusion":[193],"sudden":[195],"changes":[196],"lighting.":[198],"It":[199],"can":[200],"provide":[201],"technical":[202],"support":[203],"for":[204],"intelligent":[205],"monitoring":[206],"traffic":[208],"management.":[209]},"counts_by_year":[],"updated_date":"2026-11-08T12:12:28.789561","created_date":"2026-06-24T00:00:00"}
