A method and apparatus for target tracking

Abstract

The invention discloses a target tracking method and a device. The method comprises the following steps: in an initialization frame, a mask matrix is established according to a target area, and a spatio-temporal regularization discriminant correlation filter model is established by using space and time constraints; the multi-scale samples of the target in the initial position and rotation angle are extracted, and the scale space discriminant correlation filter model is learnt; in the subsequent frame, the target position and rotation angle are obtained by using spatio-temporal regularization discriminant correlation filter; the scale space is used to discriminate the correlation filter to obtain the target scale; according to the tracking results, the correlation filter is updated online.By using this method, the tracking robustness under occlusion, deformation and rotation of the target can be improved, and the displacement, rotation and scale of the target can be estimated, so thatthe accurate target area can be obtained, and the target can be continuously tracked. The device for realizing the target tracking of the method comprises an image acquisition unit, an image processing unit, a learning unit, a tracking unit and a servo driving unit.

Description

technical field [0001] The invention relates to the technical field of target tracking in computer vision, in particular to a method and device for target tracking. Background technique [0002] Target visual tracking is an important research direction in the field of computer vision. Its main task is to obtain the position and motion information of the target of interest in the video sequence, which provides the basis for further semantic analysis (action recognition, scene recognition, etc.), and is widely used in Robotics, intelligent transportation, security and human-computer interaction and other fields. The main difficulties in single-object visual tracking lie in light changes, object deformation, object rotation, partial occlusion, fast motion, and background interference in videos. [0003] The current target visual tracking methods are mainly divided into two categories: generative methods and discriminative methods. Generative methods search for the most simila...

AI Technical Summary

Problems solved by technology

This method can solve the problem of small detection area and insufficient discrimination in the traditional discriminant correlation filter tracking method, improve the time robustness in the case of target occlusion, deformation, rotation, etc., and estimate the displacement, rotation and scale of the target , to get accurate tracking target area, so as to continuously track the target

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