Target Tracking Based on Multi Feature Selection Fusion Compensation in Monitoring Video
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This thesis is mainly targeted at self-adaptation adjustment in the search region: at first, design a staging predation space self-adaptation scale strategy bat algorithm (AP-RBA), and then, use AP-RBA algorithm to establish a target tracking strategy of optimized particle filter which can effectively solve two kinds of problems: (1) particle impoverishment phenomena produced in particle filter; (2) effective tracking targets based on few particles, thus simplifying complexity of particle filter, and then, adopt the criterion weight strategy to achieve maximum a posteriori and change of criterion weight to realize effective improvement of particle distribution and promote efficiency of particle filter process.
Keywords:feature selection video monitoring target tracking moving background image segmentation
This work is supported by Anhui province outstanding young talents support program (gxyq2017157, gxyq2017159); Anhui province major teaching reform project (2016jyxm0777); Anhui natural science research project (KJ2017A838, KJ2017A837, KJ2018A0669, KJ2018A0670).
CONFLICT OF INTEREST
The authors declare that they have no conflicts of interest.
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