The Anti-Occlusion Correlation Filtering Tracking Algorithm Based on Edge Detection
For its convenience,tracking targets with unmanned aerial vehicles is getting more and more attention.Based on the correlation filtering algorithm,the quality of samples is optimized by edge detection,and smoothing constraints are added to the edge detection scoring link,which increases the accuracy of targets included in candi-date boxes,and achieves the effects of reducing computational complexity and improving tracking robustness.Adap-tive multi-feature fusion is used to enhance the feature expression capability,which improves the accuracy of target tracking.The occlusion detection mechanism and the adaptive updating learning rate are introduced to reduce the impact of occlusion on filtering templates,which improves the success rate of target tracking.Qualitative evaluation and quantitative evaluation are conducted through experiments on OTB-2015 and UAV123 datasets,which dem-onstrates the superiority of the studied algorithm over other tracking algorithms.
万方数据
维普
