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Moving target tracking algorithm

A tracking algorithm and moving target technology, applied in the field of moving target tracking algorithm based on particle filtering, to achieve the effect of improving practicability

Inactive Publication Date: 2014-12-03
南京恒誉名翔科技有限公司
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] From the current point of view, among the many methods studied, Kalman filtering is used in various linear conditions and Gaussian distribution noise environments, but it is powerless in nonlinear and non-Gaussian distribution noise environments.

Method used

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Experimental program
Comparison scheme
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Embodiment 1

[0027] combine figure 1 , figure 1 It is the flow chart of the particle filter algorithm of the present invention; the steps of the particle filter algorithm are summarized:

[0028] (1) Initialization

[0029] When k=0, according to ,right Take a sample.

[0030] (2) Importance function weighting

[0031] Weighting the importance weights of the particles Calculate, and then regularize,

[0032] .

[0033] (3) State estimation

[0034] .

[0035] (4) Resampling

[0036] if , resampling to get a new particle set .

Embodiment 2

[0038] figure 2 It is a flow chart of the particle filter wave-based video target tracking algorithm of the present invention. The steps of the video target tracking algorithm are as follows:

[0039] (1) Frame the target and initialize the particles. After selecting the target, calculate the color histogram of the area, set K=0 at this time, use the initial motion state of the target as the prior distribution, initialize the particle set, and get ;

[0040] (2) System state transition, in Known, calculated according to the state transition equation, ;

[0041] (3) ;

[0042] (4) Using the color histogram detection, at time k, open a tracking window in the possible particle distribution area, and then use the Bhattacharyya distance to calculate the similarity between the initial color histogram and the color histogram in the tracking window, and get ;

[0043] (5) Calculate the residual

[0044] ,

[0045] Update the weights, and calculate the weights of each...

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Abstract

The invention discloses a moving target tracking algorithm. According to the moving target tracking algorithm, the corresponding color histogram is calculated according to color information of a target, and the rough track region of particles is predicted through a state transition equation based on a one-order autoregressive model; sampling is conducted on the predicted region, the weight of each particle is calculated according to the selected importance function, and the position of the target is estimated through the particles with the large weight. According to the algorithm, the problem of particle degeneracy is solved through a resample method. The moving target tracking algorithm is suitable for the non-Gaussian distributed noise environment, and practicability of the moving target tracking algorithm is improved.

Description

technical field [0001] The invention relates to a moving target tracking algorithm, in particular to a moving target tracking algorithm based on particle filter. Background technique [0002] Target tracking refers to the technology of identifying targets entering a specific area in a certain monitoring environment and tracking the target trajectory. Object tracking technology has broad application prospects in the fields of public security, government, finance and education. In recent years, particle filter-based target tracking technology has brought a new direction to the field of target tracking because of its wider applicability and overcoming the shortcomings of traditional target tracking technology. Particle filter can play its good performance in this nonlinear environment, and the tracking performance of moving targets is better than traditional filter algorithms such as Kalman filter. [0003] From the current point of view, among the many methods studied, Kalma...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/20
Inventor 费浚纯
Owner 南京恒誉名翔科技有限公司
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