Particle swarm optimization algorithm-based tracking and locating method for multiple moving targets in video

A particle swarm optimization, multi-moving target technology, applied in the field of image processing, can solve problems such as inability to solve multi-target positioning problems, and achieve the effects of solving stagnation, reducing computing costs, and low spatial resolution

CN107169990AInactive Publication Date: 2017-09-15NANJING UNIV OF POSTS & TELECOMM
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Publication Date
2017-09-15
Estimated Expiration
Not applicable · inactive patent

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Abstract

The invention discloses a particle swarm optimization algorithm-based tracking and locating method for multiple moving targets in a video. The method comprises the steps of firstly performing image spot detection through a background difference method; and then dividing a particle swarm into particle sub-swarms by taking image spots as units, and using a particle swarm optimization algorithm in each sub-swarm to achieve the purpose of locating the multiple moving targets. According to the method, the problem of multi-target detection and the problem of difficult detection caused by object adhesion and picture darkness can be solved.
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Description

technical field

[0001] The invention relates to the technical field of image processing, in particular to a video multi-moving target tracking and positioning method based on particle swarm optimization algorithm. Background technique

[0002] Particle Swarm Optimization (PSO) is inspired by the regularity of bird cluster activities, and then uses swarm intelligence to establish a simplified model. Based on the observation of the behavior of animal clusters, particle swarm algorithm uses the information sharing of individuals in the group to make the movement of the whole group evolve from disorder to order in the problem solving space, so as to obtain the optimal solution. Similar to genetic algorithm, PSO is an optimization algorithm based on iteration. The system is initialized as a set of random solutions, and the optimal value is searched through iteration. But it does not have the crossover and mutation used by the genetic algorithm, but the particles follow the opti...

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Embodiment Construction

[0033] Below in conjunction with accompanying drawing, technical scheme of the present invention is described in further detail:

[0034] Such as figure 1 Shown is the flow chart of the video multi-moving target positioning method based on the particle swarm optimization algorithm, as follows:

[0035] Step 1), select a section of 8046-frame video sequence from the vehicle monitoring video, compress the size to 240x320 pixels, and evenly extract 40 frames of the video at the same time interval. Access each pixel of each frame by row, record the color intensity values ​​of the three channels of each pixel, calculate the grayscale value of each pixel, and convert each frame of image into a two-dimensional matrix, The two-dimensional matrix converted from the i-th frame image is denoted as I i , i∈{1,2,…,40};

[0036] Step 2), sequentially divide each frame of image into speckle pixels and background pixels to obtain the number of speckles and their geometric features, the spe...