Deep learning-based personnel retrograde running detection method in electronic escalator running process
The invention discloses a deep learning-based personnel retrograde driving detection method in an electronic escalator operation process, which comprises the following steps of: inputting a collected personnel image on an electronic escalator into a target identification network model to obtain cont...
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 | WANG YINRUI ZHANG HUAYU DAI HAOWEI LU HAIYANG CHENG YUAN LIANG ANYANG YANG MINGLUN |
| description | The invention discloses a deep learning-based personnel retrograde driving detection method in an electronic escalator operation process, which comprises the following steps of: inputting a collected personnel image on an electronic escalator into a target identification network model to obtain continuous multi-frame personnel position information; damping, filtering and matching are carried out on continuous multi-frame personnel position information, and personnel tracking information of continuous multi-frame images is obtained; and in combination with the personnel tracking information of the continuous multi-frame image and the identified running direction of the electronic escalator, a retrograde moving sample range is obtained, and the movement direction of the personnel is judged based on the retrograde moving sample range. According to the method, the deep learning technology is utilized, the image data in the operation process of the electronic escalator is learned, an algorithm and a system framewo |
| format | Patent |
| fullrecord | <record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_CN118609154A</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>CN118609154A</sourcerecordid><originalsourceid>FETCH-epo_espacenet_CN118609154A3</originalsourceid><addsrcrecordid>eNqNi70KAjEQBq-xEPUd1gc48PAHLeVUrKzsjzX57gzE3bCJ76-CWFsNDDPjKhyARBFsEmSob5zhKcGyiiCSoZgOxh5kT_kk5FHgSlChB8pdPQUhxLcyleAI2XHkovYbkqlDztNq1HPMmH05qean47U910jaISd2EJSuvTTNdrPYNevVfvlP8wLEfEGz</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>Deep learning-based personnel retrograde running detection method in electronic escalator running process</title><source>esp@cenet</source><creator>WANG YINRUI ; ZHANG HUAYU ; DAI HAOWEI ; LU HAIYANG ; CHENG YUAN ; LIANG ANYANG ; YANG MINGLUN</creator><creatorcontrib>WANG YINRUI ; ZHANG HUAYU ; DAI HAOWEI ; LU HAIYANG ; CHENG YUAN ; LIANG ANYANG ; YANG MINGLUN</creatorcontrib><description>The invention discloses a deep learning-based personnel retrograde driving detection method in an electronic escalator operation process, which comprises the following steps of: inputting a collected personnel image on an electronic escalator into a target identification network model to obtain continuous multi-frame personnel position information; damping, filtering and matching are carried out on continuous multi-frame personnel position information, and personnel tracking information of continuous multi-frame images is obtained; and in combination with the personnel tracking information of the continuous multi-frame image and the identified running direction of the electronic escalator, a retrograde moving sample range is obtained, and the movement direction of the personnel is judged based on the retrograde moving sample range. According to the method, the deep learning technology is utilized, the image data in the operation process of the electronic escalator is learned, an algorithm and a system framewo</description><language>chi ; eng</language><subject>CALCULATING ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; COUNTING ; IMAGE DATA PROCESSING OR GENERATION, IN GENERAL ; PHYSICS</subject><creationdate>2024</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=20240906&DB=EPODOC&CC=CN&NR=118609154A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,776,881,25542,76516</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20240906&DB=EPODOC&CC=CN&NR=118609154A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>WANG YINRUI</creatorcontrib><creatorcontrib>ZHANG HUAYU</creatorcontrib><creatorcontrib>DAI HAOWEI</creatorcontrib><creatorcontrib>LU HAIYANG</creatorcontrib><creatorcontrib>CHENG YUAN</creatorcontrib><creatorcontrib>LIANG ANYANG</creatorcontrib><creatorcontrib>YANG MINGLUN</creatorcontrib><title>Deep learning-based personnel retrograde running detection method in electronic escalator running process</title><description>The invention discloses a deep learning-based personnel retrograde driving detection method in an electronic escalator operation process, which comprises the following steps of: inputting a collected personnel image on an electronic escalator into a target identification network model to obtain continuous multi-frame personnel position information; damping, filtering and matching are carried out on continuous multi-frame personnel position information, and personnel tracking information of continuous multi-frame images is obtained; and in combination with the personnel tracking information of the continuous multi-frame image and the identified running direction of the electronic escalator, a retrograde moving sample range is obtained, and the movement direction of the personnel is judged based on the retrograde moving sample range. According to the method, the deep learning technology is utilized, the image data in the operation process of the electronic escalator is learned, an algorithm and a system framewo</description><subject>CALCULATING</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>IMAGE DATA PROCESSING OR GENERATION, IN GENERAL</subject><subject>PHYSICS</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2024</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNi70KAjEQBq-xEPUd1gc48PAHLeVUrKzsjzX57gzE3bCJ76-CWFsNDDPjKhyARBFsEmSob5zhKcGyiiCSoZgOxh5kT_kk5FHgSlChB8pdPQUhxLcyleAI2XHkovYbkqlDztNq1HPMmH05qean47U910jaISd2EJSuvTTNdrPYNevVfvlP8wLEfEGz</recordid><startdate>20240906</startdate><enddate>20240906</enddate><creator>WANG YINRUI</creator><creator>ZHANG HUAYU</creator><creator>DAI HAOWEI</creator><creator>LU HAIYANG</creator><creator>CHENG YUAN</creator><creator>LIANG ANYANG</creator><creator>YANG MINGLUN</creator><scope>EVB</scope></search><sort><creationdate>20240906</creationdate><title>Deep learning-based personnel retrograde running detection method in electronic escalator running process</title><author>WANG YINRUI ; ZHANG HUAYU ; DAI HAOWEI ; LU HAIYANG ; CHENG YUAN ; LIANG ANYANG ; YANG MINGLUN</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN118609154A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2024</creationdate><topic>CALCULATING</topic><topic>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>IMAGE DATA PROCESSING OR GENERATION, IN GENERAL</topic><topic>PHYSICS</topic><toplevel>online_resources</toplevel><creatorcontrib>WANG YINRUI</creatorcontrib><creatorcontrib>ZHANG HUAYU</creatorcontrib><creatorcontrib>DAI HAOWEI</creatorcontrib><creatorcontrib>LU HAIYANG</creatorcontrib><creatorcontrib>CHENG YUAN</creatorcontrib><creatorcontrib>LIANG ANYANG</creatorcontrib><creatorcontrib>YANG MINGLUN</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>WANG YINRUI</au><au>ZHANG HUAYU</au><au>DAI HAOWEI</au><au>LU HAIYANG</au><au>CHENG YUAN</au><au>LIANG ANYANG</au><au>YANG MINGLUN</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Deep learning-based personnel retrograde running detection method in electronic escalator running process</title><date>2024-09-06</date><risdate>2024</risdate><abstract>The invention discloses a deep learning-based personnel retrograde driving detection method in an electronic escalator operation process, which comprises the following steps of: inputting a collected personnel image on an electronic escalator into a target identification network model to obtain continuous multi-frame personnel position information; damping, filtering and matching are carried out on continuous multi-frame personnel position information, and personnel tracking information of continuous multi-frame images is obtained; and in combination with the personnel tracking information of the continuous multi-frame image and the identified running direction of the electronic escalator, a retrograde moving sample range is obtained, and the movement direction of the personnel is judged based on the retrograde moving sample range. According to the method, the deep learning technology is utilized, the image data in the operation process of the electronic escalator is learned, an algorithm and a system framewo</abstract><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | |
| ispartof | |
| issn | |
| language | chi ; eng |
| recordid | cdi_epo_espacenet_CN118609154A |
| source | esp@cenet |
| subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING IMAGE DATA PROCESSING OR GENERATION, IN GENERAL PHYSICS |
| title | Deep learning-based personnel retrograde running detection method in electronic escalator running process |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-21T18%3A03%3A35IST&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=WANG%20YINRUI&rft.date=2024-09-06&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3ECN118609154A%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 |