Infrared image vehicle detection method
The invention relates to an infrared image vehicle detection method, and belongs to the technical field of image processing. According to the method, a single-frame image is acquired from an infrared monitoring video stream and input into a deep learning network model for vehicle detection; meanwhil...
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| creator | GAO HAOLIN ZHANG JIE XU MIAOYU LIU ZHENZHEN WANG KUN CHEN ZHAOYANG |
| description | The invention relates to an infrared image vehicle detection method, and belongs to the technical field of image processing. According to the method, a single-frame image is acquired from an infrared monitoring video stream and input into a deep learning network model for vehicle detection; meanwhile, a sequence frame image is obtained in the infrared real-time monitoring video stream, and movement detection is carried out; and if a target is detected, inputting the target into a deep learning network model for vehicle detection. According to the method, two modes of static target detection and moving target detection are combined, and a single-frame image detection method and a sequence frame image detection method are adopted, so that vehicle target detection under an infrared imaging condition is realized, and the infrared image vehicle detection accuracy is improved.
本发明涉及一种红外图像车辆检测方法，属于图像处理技术领域。本发明在红外监控视频流中获取单帧图像，输入到深度学习网络模型进行车辆检测；同时在红外实时监控视频流中获取序列帧图像，进行移动侦测检测；如果检测到目标，则输入到深度学习网络模型进行车辆检测。本发明结合静目标检测和动目标检测两 |
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本发明涉及一种红外图像车辆检测方法，属于图像处理技术领域。本发明在红外监控视频流中获取单帧图像，输入到深度学习网络模型进行车辆检测；同时在红外实时监控视频流中获取序列帧图像，进行移动侦测检测；如果检测到目标，则输入到深度学习网络模型进行车辆检测。本发明结合静目标检测和动目标检测两</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>2022</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=20221125&DB=EPODOC&CC=CN&NR=115393254A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25564,76547</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20221125&DB=EPODOC&CC=CN&NR=115393254A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>GAO HAOLIN</creatorcontrib><creatorcontrib>ZHANG JIE</creatorcontrib><creatorcontrib>XU MIAOYU</creatorcontrib><creatorcontrib>LIU ZHENZHEN</creatorcontrib><creatorcontrib>WANG KUN</creatorcontrib><creatorcontrib>CHEN ZHAOYANG</creatorcontrib><title>Infrared image vehicle detection method</title><description>The invention relates to an infrared image vehicle detection method, and belongs to the technical field of image processing. According to the method, a single-frame image is acquired from an infrared monitoring video stream and input into a deep learning network model for vehicle detection; meanwhile, a sequence frame image is obtained in the infrared real-time monitoring video stream, and movement detection is carried out; and if a target is detected, inputting the target into a deep learning network model for vehicle detection. According to the method, two modes of static target detection and moving target detection are combined, and a single-frame image detection method and a sequence frame image detection method are adopted, so that vehicle target detection under an infrared imaging condition is realized, and the infrared image vehicle detection accuracy is improved.
本发明涉及一种红外图像车辆检测方法，属于图像处理技术领域。本发明在红外监控视频流中获取单帧图像，输入到深度学习网络模型进行车辆检测；同时在红外实时监控视频流中获取序列帧图像，进行移动侦测检测；如果检测到目标，则输入到深度学习网络模型进行车辆检测。本发明结合静目标检测和动目标检测两</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>2022</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZFD3zEsrSixKTVHIzE1MT1UoS83ITM5JVUhJLUlNLsnMz1PITS3JyE_hYWBNS8wpTuWF0twMim6uIc4euqkF-fGpxQWJyal5qSXxzn6GhqbGlsZGpiaOxsSoAQCXlSfe</recordid><startdate>20221125</startdate><enddate>20221125</enddate><creator>GAO HAOLIN</creator><creator>ZHANG JIE</creator><creator>XU MIAOYU</creator><creator>LIU ZHENZHEN</creator><creator>WANG KUN</creator><creator>CHEN ZHAOYANG</creator><scope>EVB</scope></search><sort><creationdate>20221125</creationdate><title>Infrared image vehicle detection method</title><author>GAO HAOLIN ; ZHANG JIE ; XU MIAOYU ; LIU ZHENZHEN ; WANG KUN ; CHEN ZHAOYANG</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN115393254A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2022</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>GAO HAOLIN</creatorcontrib><creatorcontrib>ZHANG JIE</creatorcontrib><creatorcontrib>XU MIAOYU</creatorcontrib><creatorcontrib>LIU ZHENZHEN</creatorcontrib><creatorcontrib>WANG KUN</creatorcontrib><creatorcontrib>CHEN ZHAOYANG</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>GAO HAOLIN</au><au>ZHANG JIE</au><au>XU MIAOYU</au><au>LIU ZHENZHEN</au><au>WANG KUN</au><au>CHEN ZHAOYANG</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Infrared image vehicle detection method</title><date>2022-11-25</date><risdate>2022</risdate><abstract>The invention relates to an infrared image vehicle detection method, and belongs to the technical field of image processing. According to the method, a single-frame image is acquired from an infrared monitoring video stream and input into a deep learning network model for vehicle detection; meanwhile, a sequence frame image is obtained in the infrared real-time monitoring video stream, and movement detection is carried out; and if a target is detected, inputting the target into a deep learning network model for vehicle detection. According to the method, two modes of static target detection and moving target detection are combined, and a single-frame image detection method and a sequence frame image detection method are adopted, so that vehicle target detection under an infrared imaging condition is realized, and the infrared image vehicle detection accuracy is improved.
本发明涉及一种红外图像车辆检测方法，属于图像处理技术领域。本发明在红外监控视频流中获取单帧图像，输入到深度学习网络模型进行车辆检测；同时在红外实时监控视频流中获取序列帧图像，进行移动侦测检测；如果检测到目标，则输入到深度学习网络模型进行车辆检测。本发明结合静目标检测和动目标检测两</abstract><oa>free_for_read</oa></addata></record> |
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| subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING IMAGE DATA PROCESSING OR GENERATION, IN GENERAL PHYSICS |
| title | Infrared image vehicle detection method |
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