Optimization of Moving Target Tracking Algorithm Based on Computer Vision
Motion target tracking is a hot topic in the field of computer vision,widely used in various scenarios such as traffic roads,shopping mall monitoring,agricultural production,national defense and military.Maintaining stability and accuracy in tracking moving targets in complex environments is currently the focus of researchers'attention.In motion target tracking algorithms,TLD algorithm has good performance and can perform effective tracking for a long time,but it has certain limitations such as being easily interfered with and slow processing speed.This article proposes an optimized motion target tracking algorithm,which mainly utilizes the KCF algorithm to optimize the TLD algorithm tracker,and then combines the existing detector and learning module to generate a new algorithm.Experimental results have shown that compared to the original algorithm,the optimized motion target tracking algorithm has significantly improved tracking accuracy and processing speed.
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维普
