Multi-feature fusion and scale adaptive kernel correlation filter tracking method

Abstract

The invention relates to a multi-feature fusion and scale adaptive kernel correlation filter tracking method, which obtains initial information of a target. The FHOG feature of a fusion gradient histogram and the CN feature of color attribute after dimension reduction of a target area are obtained. The thirty-one-dimensional FHOG feature, the post-dimension reduction two-dimensional CN feature andone-dimensional gray feature are fushed by linear fusion so that totally thirty-four features are used as the final feature map after fusion. On the basis of the fusion feature map, the translationalposition of the target is predicted by using the kernel correlation filter. After the translation position is predicted, scale filter is added to predict the scale change of the target. After predicting the translational position and scale of the target, two filter templates are updated by linear interpolation method and tracked until the last frame. Through the combination of feature fusion andscale filter, the method has good robustness in the case of distortion, scale change, illumination change, background similar disturbance and so on in the process of target tracking.

Description

technical field [0001] The invention relates to a target tracking technology, in particular to a multi-feature fusion and scale adaptive kernel correlation filter tracking method. Background technique [0002] Object tracking is widely used in video surveillance, intelligent transportation systems and human-computer interaction and other fields. However, there are still many problems and difficulties in the existing target tracking methods. Appearance deformation, illumination changes, fast motion, motion blur, similar background interference, etc. all have a great impact on tracking. At present, there is no tracking model that can be both good and efficient. Solve these problems quickly. At present, the main tracking models can be divided into two categories: generative models and discriminative models. The generation model is to model the initial target area, and find the area most similar to the model in the next frame, that is, the prediction area. The center of gravi...

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Problems solved by technology

[0004] The present invention is aimed at the problems of appearance deformation, illumination change, fast motion, motion blur and similar background interference in visual target tracking, and proposes a multi-feature fusion and scale-adaptive kernel correlation filter tracking method. Based on the fusion of FHOG features and CN features, the feature map of the target is greatly enriched, and the change of the translation position of the target can be predicted more accurately. On the basis of predicting the translation position of the target, it is predicted by adding a scale filter of 33 scales target scale change

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