A Template Matching Tracking Method Based on Particle Swarm Optimization

Abstract

The invention discloses a template matching tracking method based on particle swarm optimization. The method comprises the steps of firstly predicting the position where a target is possibly located in a current frame according to movement conditions of the target in the past, wherein each type of prediction is represented by a particle in a particle swarm optimization algorithm, and the position and the range of the target are used to act a searching space of the particle swarm optimization algorithm; and secondly, searching a target state value with the maximum correlation matching value in a state searching space by using a particle swarm optimization searching algorithm to act as a result of target tracking, and adaptively updating a template according to the tracking result so as to realize continuous and steady tracking. According to the invention, the particle swarm optimization searching method is adopted to search in the target state space, and target template matching is carried out so as to acquire the tracking result of the current frame. The method disclosed by the invention can well improve the robustness of a tracking algorithm, and greatly reduces the complexity of the algorithm.

Description

technical field [0001] The invention belongs to the technical field of template matching, and in particular relates to a template matching tracking method based on particle swarm optimization. Background technique [0002] Video object tracking refers to determining the position, size, speed and other motion parameters and trajectory of a specific object of interest in the image in the video frame sequence according to the visual characteristics of the object in the video. Video object tracking is one of the core tasks of computer vision systems, and it has broad application prospects in many fields such as intelligent video surveillance, human-computer interaction, medical diagnosis, and robot navigation. However, in practice, the robustness of complex scenes and the real-time requirements of tracking algorithms are the main challenges of current video object tracking technology. Therefore, how to improve the accuracy and real-time performance of tracking technology to ada...

AI Technical Summary

Problems solved by technology

[0009] The object of the present invention is to provide a template matching tracking method based on particle swarm optimization, which aims to solve the problem that the existing template matching has high computational complexity, and the search method from coarse to fine is also easy to fall into local optimum, and the obtained matching The problem with the result is not the optimal result

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