Visual target tracking method based on scale adaptation and occlusion detection

Abstract

The invention relates to a visual target tracking method based on scale adaptation and occlusion detection. The method comprises the following steps of according to a target position and a size determined by a previous frame, cutting an image block in a current frame and extracting the convolution characteristics of different layers as sample characteristic graphs; in each layer of the characteristic graph, using a nuclear correlation filtering method to acquire a response graph, and then linearly superposing the different layers of response graphs to acquire a response general graph, whereina position corresponding to a maximum value is a the target position of a current frame; collecting different sizes of samples at the target position and adjusting to a same size, and acquiring a scale response via a scale filter, wherein a scale corresponding to a maximum value is the optimum scale of the current frame; calculating the peak value side lobe ratio of the response general graph anddetermining whether a target is occluded; when the target is occluded, using a space-time context model to re-determine the target position; and updating the model and preparing for the determinationof the target position and the size of the next frame. In the invention, the accuracy and the robustness of visual target tracking are increased.

Description

technical field [0001] The invention relates to the technical field of visual target tracking, in particular to a visual target tracking method based on scale adaptation and occlusion detection. Background technique [0002] Visual object tracking is a challenging task in computer vision, which is widely used in video surveillance, human-computer interaction, medical imaging, and robotics. Visual object tracking gives the location and bounding box of the object in the first frame of the video, and then estimates the location and bounding box of the object in each subsequent frame. Since objects are prone to appearance changes in videos, such as scale changes, occlusions, illumination changes, rotations, etc., there is no object tracking method that can be adapted to all tracking scenarios at this stage. [0003] At present, in the research of visual target tracking, the features used are mainly hand-designed features, such as gradient histogram (histogram of orientation gra...

AI Technical Summary

Problems solved by technology

[0004] The technical problem to be solved by the present invention is to provide a visual target tracking method based on scale adaptation and occlusion detection, which can solve the problems of target scale change and occlusion, thereby improving the accuracy and robustness of visual target tracking

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