Pedestrian trajectory prediction method and device based on adversarial network, equipment and medium
The invention discloses a pedestrian trajectory prediction method and device based on an adversarial network, equipment and a medium, and the method comprises the steps: obtaining past historical trajectory information and real future trajectory information of a current pedestrian, and carrying out...
Gespeichert in:
| Hauptverfasser: | , , , , , , , , |
|---|---|
| Format: | Patent |
| Sprache: | chi ; eng |
| Schlagworte: | |
| Online-Zugang: | Volltext bestellen |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | |
|---|---|
| container_issue | |
| container_start_page | |
| container_title | |
| container_volume | |
| creator | LI JIADI ZHU MING YANG QIANG WANG JIAWEI ZHANG GEXIANG MA ZHONGLI LIU QIYU LUO DENING QUAN XUEFENG |
| description | The invention discloses a pedestrian trajectory prediction method and device based on an adversarial network, equipment and a medium, and the method comprises the steps: obtaining past historical trajectory information and real future trajectory information of a current pedestrian, and carrying out the coding processing of the historical trajectory information, and obtaining a pedestrian motion state of the current pedestrian; processing the pedestrian motion state by using a social attention mechanism to obtain weight information of the current pedestrian, and obtaining predicted future trajectory information of the current pedestrian by using the weight information; performing auxiliary mutual information function processing on the predicted future trajectory information and the real future trajectory information to generate a loss function, and performing training optimization on an adversarial network by using the loss function to obtain a trained and optimized adversarial network; and performing pedestri |
| format | Patent |
| fullrecord | <record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_CN115908490A</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>CN115908490A</sourcerecordid><originalsourceid>FETCH-epo_espacenet_CN115908490A3</originalsourceid><addsrcrecordid>eNqNzL0OAUEUBeBtFIJ3uHqS3SCxpWyIShR6uWaOGHZ-zNxd8fYm4gFUpzjnO8MCR2gkiYYdSeQ7lPj4phChjRLjHVnIzWtip0mjNwp04QRNuWLdIybOuCUHefn4mBGenQkWTr7E5p_OjovBlduEyS9HxXS3PTX7OYI_IwVWyP7cHKpqVZfrZV1uFv9sPnbxP60</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>Pedestrian trajectory prediction method and device based on adversarial network, equipment and medium</title><source>esp@cenet</source><creator>LI JIADI ; ZHU MING ; YANG QIANG ; WANG JIAWEI ; ZHANG GEXIANG ; MA ZHONGLI ; LIU QIYU ; LUO DENING ; QUAN XUEFENG</creator><creatorcontrib>LI JIADI ; ZHU MING ; YANG QIANG ; WANG JIAWEI ; ZHANG GEXIANG ; MA ZHONGLI ; LIU QIYU ; LUO DENING ; QUAN XUEFENG</creatorcontrib><description>The invention discloses a pedestrian trajectory prediction method and device based on an adversarial network, equipment and a medium, and the method comprises the steps: obtaining past historical trajectory information and real future trajectory information of a current pedestrian, and carrying out the coding processing of the historical trajectory information, and obtaining a pedestrian motion state of the current pedestrian; processing the pedestrian motion state by using a social attention mechanism to obtain weight information of the current pedestrian, and obtaining predicted future trajectory information of the current pedestrian by using the weight information; performing auxiliary mutual information function processing on the predicted future trajectory information and the real future trajectory information to generate a loss function, and performing training optimization on an adversarial network by using the loss function to obtain a trained and optimized adversarial network; and performing pedestri</description><language>chi ; eng</language><subject>CALCULATING ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; COUNTING ; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES ; IMAGE DATA PROCESSING OR GENERATION, IN GENERAL ; PHYSICS ; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR</subject><creationdate>2023</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20230404&DB=EPODOC&CC=CN&NR=115908490A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,776,881,25543,76294</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20230404&DB=EPODOC&CC=CN&NR=115908490A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>LI JIADI</creatorcontrib><creatorcontrib>ZHU MING</creatorcontrib><creatorcontrib>YANG QIANG</creatorcontrib><creatorcontrib>WANG JIAWEI</creatorcontrib><creatorcontrib>ZHANG GEXIANG</creatorcontrib><creatorcontrib>MA ZHONGLI</creatorcontrib><creatorcontrib>LIU QIYU</creatorcontrib><creatorcontrib>LUO DENING</creatorcontrib><creatorcontrib>QUAN XUEFENG</creatorcontrib><title>Pedestrian trajectory prediction method and device based on adversarial network, equipment and medium</title><description>The invention discloses a pedestrian trajectory prediction method and device based on an adversarial network, equipment and a medium, and the method comprises the steps: obtaining past historical trajectory information and real future trajectory information of a current pedestrian, and carrying out the coding processing of the historical trajectory information, and obtaining a pedestrian motion state of the current pedestrian; processing the pedestrian motion state by using a social attention mechanism to obtain weight information of the current pedestrian, and obtaining predicted future trajectory information of the current pedestrian by using the weight information; performing auxiliary mutual information function processing on the predicted future trajectory information and the real future trajectory information to generate a loss function, and performing training optimization on an adversarial network by using the loss function to obtain a trained and optimized adversarial network; and performing pedestri</description><subject>CALCULATING</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES</subject><subject>IMAGE DATA PROCESSING OR GENERATION, IN GENERAL</subject><subject>PHYSICS</subject><subject>SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2023</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNzL0OAUEUBeBtFIJ3uHqS3SCxpWyIShR6uWaOGHZ-zNxd8fYm4gFUpzjnO8MCR2gkiYYdSeQ7lPj4phChjRLjHVnIzWtip0mjNwp04QRNuWLdIybOuCUHefn4mBGenQkWTr7E5p_OjovBlduEyS9HxXS3PTX7OYI_IwVWyP7cHKpqVZfrZV1uFv9sPnbxP60</recordid><startdate>20230404</startdate><enddate>20230404</enddate><creator>LI JIADI</creator><creator>ZHU MING</creator><creator>YANG QIANG</creator><creator>WANG JIAWEI</creator><creator>ZHANG GEXIANG</creator><creator>MA ZHONGLI</creator><creator>LIU QIYU</creator><creator>LUO DENING</creator><creator>QUAN XUEFENG</creator><scope>EVB</scope></search><sort><creationdate>20230404</creationdate><title>Pedestrian trajectory prediction method and device based on adversarial network, equipment and medium</title><author>LI JIADI ; ZHU MING ; YANG QIANG ; WANG JIAWEI ; ZHANG GEXIANG ; MA ZHONGLI ; LIU QIYU ; LUO DENING ; QUAN XUEFENG</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN115908490A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2023</creationdate><topic>CALCULATING</topic><topic>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES</topic><topic>IMAGE DATA PROCESSING OR GENERATION, IN GENERAL</topic><topic>PHYSICS</topic><topic>SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR</topic><toplevel>online_resources</toplevel><creatorcontrib>LI JIADI</creatorcontrib><creatorcontrib>ZHU MING</creatorcontrib><creatorcontrib>YANG QIANG</creatorcontrib><creatorcontrib>WANG JIAWEI</creatorcontrib><creatorcontrib>ZHANG GEXIANG</creatorcontrib><creatorcontrib>MA ZHONGLI</creatorcontrib><creatorcontrib>LIU QIYU</creatorcontrib><creatorcontrib>LUO DENING</creatorcontrib><creatorcontrib>QUAN XUEFENG</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>LI JIADI</au><au>ZHU MING</au><au>YANG QIANG</au><au>WANG JIAWEI</au><au>ZHANG GEXIANG</au><au>MA ZHONGLI</au><au>LIU QIYU</au><au>LUO DENING</au><au>QUAN XUEFENG</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Pedestrian trajectory prediction method and device based on adversarial network, equipment and medium</title><date>2023-04-04</date><risdate>2023</risdate><abstract>The invention discloses a pedestrian trajectory prediction method and device based on an adversarial network, equipment and a medium, and the method comprises the steps: obtaining past historical trajectory information and real future trajectory information of a current pedestrian, and carrying out the coding processing of the historical trajectory information, and obtaining a pedestrian motion state of the current pedestrian; processing the pedestrian motion state by using a social attention mechanism to obtain weight information of the current pedestrian, and obtaining predicted future trajectory information of the current pedestrian by using the weight information; performing auxiliary mutual information function processing on the predicted future trajectory information and the real future trajectory information to generate a loss function, and performing training optimization on an adversarial network by using the loss function to obtain a trained and optimized adversarial network; and performing pedestri</abstract><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | |
| ispartof | |
| issn | |
| language | chi ; eng |
| recordid | cdi_epo_espacenet_CN115908490A |
| source | esp@cenet |
| subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES IMAGE DATA PROCESSING OR GENERATION, IN GENERAL PHYSICS SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR |
| title | Pedestrian trajectory prediction method and device based on adversarial network, equipment and medium |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-23T07%3A49%3A08IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-epo_EVB&rft_val_fmt=info:ofi/fmt:kev:mtx:patent&rft.genre=patent&rft.au=LI%20JIADI&rft.date=2023-04-04&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3ECN115908490A%3C/epo_EVB%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true |