基于响应值判断的目标跟踪 ECO 方法

Target tracking ECO (Efficient Convolution Operator) method is more and more widely used in various tracking scenes because of its superior tracking performance, but it shows poor tracking effect in the face of complex engineering practical situations such as occlusion, motion blur, target deformation and background clutters. To solve this problem, the ECO method was improved, and a correlation filter response value judgment mechanism was added to determine the update time of the sample model according to the maximum response mean of the previous frames and the standard deviation of the response peak of the current frame. Comparing with the original ECO method based on the same experimental video sequence, the tracking effect of the improved ECO method was showed. On OTB2015 data set, the accuracy and success rate of the improved ECO method can reach up to 88.0% and 79.9%, 1.5% and 1.2% higher than the original ECO method respectively, especially in common engineering situations such as occlusion, motion blur and background clutters. It shows that this method can provide more flexible model updating strategy and stronger ability to adapt to the actual situation of complex engineering.