BP-PMBM filtering algorithm-based multi-target tracking method
The invention discloses a BP-PMBM filtering algorithm-based multi-target tracking method. The method comprises the following steps of: (1) initializing an algorithm; (2) predicting a target state; (3) updating the target state; (4) trimming the Poisson component and the MBM component in the target s...
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| creator | HE YUQI LI QINLEI CHAI JIABO SONG LIPING XING TIANPENG WANG FEIFEI LIU HAONAN |
| description | The invention discloses a BP-PMBM filtering algorithm-based multi-target tracking method. The method comprises the following steps of: (1) initializing an algorithm; (2) predicting a target state; (3) updating the target state; (4) trimming the Poisson component and the MBM component in the target state; (5) carrying out box particle re-sampling on the Poisson component and the MBM component; (6) estimating the target state to obtain a global target state estimation value. The BP-PMBM filtering algorithm-based multi-target tracking method provided by the invention has the advantages of high tracking precision, high operation speed, capability of distinguishing tracks and the like.
本发明公开了一种基于BP-PMBM滤波算法的多目标跟踪方法，包括：(1)初始化算法；(2)对目标状态进行预测；(3)更新所述目标状态；(4)对所述目标状态中的Poisson分量和MBM分量进行修剪；(5)对所述Poisson分量和所述MBM分量进行箱粒子重采样；(6)对所述目标状态进行估计，得到全局目标状态估计值。本发明提供的基于BP-PMBM滤波算法的多目标跟踪方法具有跟踪精度高、运算速度快、可区分航迹等优点。 |
| format | Patent |
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本发明公开了一种基于BP-PMBM滤波算法的多目标跟踪方法，包括：(1)初始化算法；(2)对目标状态进行预测；(3)更新所述目标状态；(4)对所述目标状态中的Poisson分量和MBM分量进行修剪；(5)对所述Poisson分量和所述MBM分量进行箱粒子重采样；(6)对所述目标状态进行估计，得到全局目标状态估计值。本发明提供的基于BP-PMBM滤波算法的多目标跟踪方法具有跟踪精度高、运算速度快、可区分航迹等优点。</description><language>chi ; eng</language><subject>CALCULATING ; COMPUTING ; COUNTING ; IMAGE DATA PROCESSING OR GENERATION, IN GENERAL ; PHYSICS</subject><creationdate>2021</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=20210917&DB=EPODOC&CC=CN&NR=113409363A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25564,76547</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20210917&DB=EPODOC&CC=CN&NR=113409363A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>HE YUQI</creatorcontrib><creatorcontrib>LI QINLEI</creatorcontrib><creatorcontrib>CHAI JIABO</creatorcontrib><creatorcontrib>SONG LIPING</creatorcontrib><creatorcontrib>XING TIANPENG</creatorcontrib><creatorcontrib>WANG FEIFEI</creatorcontrib><creatorcontrib>LIU HAONAN</creatorcontrib><title>BP-PMBM filtering algorithm-based multi-target tracking method</title><description>The invention discloses a BP-PMBM filtering algorithm-based multi-target tracking method. The method comprises the following steps of: (1) initializing an algorithm; (2) predicting a target state; (3) updating the target state; (4) trimming the Poisson component and the MBM component in the target state; (5) carrying out box particle re-sampling on the Poisson component and the MBM component; (6) estimating the target state to obtain a global target state estimation value. The BP-PMBM filtering algorithm-based multi-target tracking method provided by the invention has the advantages of high tracking precision, high operation speed, capability of distinguishing tracks and the like.
本发明公开了一种基于BP-PMBM滤波算法的多目标跟踪方法，包括：(1)初始化算法；(2)对目标状态进行预测；(3)更新所述目标状态；(4)对所述目标状态中的Poisson分量和MBM分量进行修剪；(5)对所述Poisson分量和所述MBM分量进行箱粒子重采样；(6)对所述目标状态进行估计，得到全局目标状态估计值。本发明提供的基于BP-PMBM滤波算法的多目标跟踪方法具有跟踪精度高、运算速度快、可区分航迹等优点。</description><subject>CALCULATING</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>2021</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZLBzCtAN8HXyVUjLzClJLcrMS1dIzEnPL8osycjVTUosTk1RyC3NKcnULUksSk8tUSgpSkzOBqnKTS3JyE_hYWBNS8wpTuWF0twMim6uIc4euqkF-fGpxQWJyal5qSXxzn6GhsYmBpbGZsaOxsSoAQAMDDAW</recordid><startdate>20210917</startdate><enddate>20210917</enddate><creator>HE YUQI</creator><creator>LI QINLEI</creator><creator>CHAI JIABO</creator><creator>SONG LIPING</creator><creator>XING TIANPENG</creator><creator>WANG FEIFEI</creator><creator>LIU HAONAN</creator><scope>EVB</scope></search><sort><creationdate>20210917</creationdate><title>BP-PMBM filtering algorithm-based multi-target tracking method</title><author>HE YUQI ; LI QINLEI ; CHAI JIABO ; SONG LIPING ; XING TIANPENG ; WANG FEIFEI ; LIU HAONAN</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN113409363A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2021</creationdate><topic>CALCULATING</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>IMAGE DATA PROCESSING OR GENERATION, IN GENERAL</topic><topic>PHYSICS</topic><toplevel>online_resources</toplevel><creatorcontrib>HE YUQI</creatorcontrib><creatorcontrib>LI QINLEI</creatorcontrib><creatorcontrib>CHAI JIABO</creatorcontrib><creatorcontrib>SONG LIPING</creatorcontrib><creatorcontrib>XING TIANPENG</creatorcontrib><creatorcontrib>WANG FEIFEI</creatorcontrib><creatorcontrib>LIU HAONAN</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>HE YUQI</au><au>LI QINLEI</au><au>CHAI JIABO</au><au>SONG LIPING</au><au>XING TIANPENG</au><au>WANG FEIFEI</au><au>LIU HAONAN</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>BP-PMBM filtering algorithm-based multi-target tracking method</title><date>2021-09-17</date><risdate>2021</risdate><abstract>The invention discloses a BP-PMBM filtering algorithm-based multi-target tracking method. The method comprises the following steps of: (1) initializing an algorithm; (2) predicting a target state; (3) updating the target state; (4) trimming the Poisson component and the MBM component in the target state; (5) carrying out box particle re-sampling on the Poisson component and the MBM component; (6) estimating the target state to obtain a global target state estimation value. The BP-PMBM filtering algorithm-based multi-target tracking method provided by the invention has the advantages of high tracking precision, high operation speed, capability of distinguishing tracks and the like.
本发明公开了一种基于BP-PMBM滤波算法的多目标跟踪方法，包括：(1)初始化算法；(2)对目标状态进行预测；(3)更新所述目标状态；(4)对所述目标状态中的Poisson分量和MBM分量进行修剪；(5)对所述Poisson分量和所述MBM分量进行箱粒子重采样；(6)对所述目标状态进行估计，得到全局目标状态估计值。本发明提供的基于BP-PMBM滤波算法的多目标跟踪方法具有跟踪精度高、运算速度快、可区分航迹等优点。</abstract><oa>free_for_read</oa></addata></record> |
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| subjects | CALCULATING COMPUTING COUNTING IMAGE DATA PROCESSING OR GENERATION, IN GENERAL PHYSICS |
| title | BP-PMBM filtering algorithm-based multi-target tracking method |
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