Target tracking method based on improved double-center particle swarm optimization algorithm

Abstract

The invention belongs to the technical field of digital image processing, and particularly relates to a target tracking method based on an improved double-center particle swarm optimization algorithm.Firstly, a target position of a first frame image in an image sequence is selected; according to the selected target, Hu invariant moment for the image of the target area to describe the shape feature of the target; meanwhile, calculating an HSV color histogram for the image of the target area is calculated according to the framed target to describe the color characteristics of the target; then,the calculated shape feature vector H and color feature vector G are connected in series to obtain a target feature vector [H, G] after feature fusion, namely target template features; then, a double-center particle swarm optimization algorithm is applied to subsequent image frames, and the positions of globally optimal particles in the image frames are obtained; and finally, the proposed anti-occlusion target template updating strategy is utilized to obtain updated new target template features. The method provided by the invention has good tracking accuracy for the target, and has good real-time performance, shielding resistance and robustness for target tracking.

Description

technical field [0001] The invention belongs to the technical field of digital image processing, and in particular relates to a target tracking method based on an improved double-center particle swarm optimization algorithm. Background technique [0002] The main task of object tracking is to locate the moving object of interest in a video sequence and form the trajectory of the object's movement. Object tracking technology is produced in the image analysis and application of moving objects, and has become an important research hotspot in the field of computer vision. At present, the traditional target tracking methods mainly include frame difference method, optical flow method, correlation tracking method, Kalman filter method, particle filter tracking method and so on. However, the frame difference method may produce holes inside the target for larger moving targets with consistent colors, and the moving target cannot be completely extracted. The optical flow method is l...

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Problems solved by technology

[0005] Aiming at the deficiencies in the above-mentioned prior art, the present invention proposes a simple, accurate and easy-to-implement engineering-based target tracking method based on the improved dual-center particle swarm optimization algorithm, aiming at solving the various characteristics of the target itself, premature convergence of particles and tracking The occlusion problem in the process

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