Real-time color object tracking method

Abstract

The invention discloses a real-time color object tracking method. The method comprises the following steps: selecting a target template under the particle filtering frame, and initializing a particleset; obtaining a current frame, and obtaining a new particle set through a state transfer model; extracting the target color information and movement information, carrying out the drifting of each particle of the new particle set through an improved mean value drift algorithm, and obtaining a particle set after drifting; building a new observation model based on the fusion of the target color information and the movement information, and calculating the particle weight of the particle seat after drifting; carrying out the normalization of the particle weight, and obtaining the state of the current frame through the weighing of the particles. The method provided by the invention can iron out the defect that the particle filtering calculation burden is large, can inhibit the background interference, and achieves the stable and real-time tracking of a target.

Description

technical field [0001] The invention relates to the field of image processing, in particular to a real-time color target tracking method. Background technique [0002] Particle filter has developed rapidly in the field of target tracking and has achieved good results. However, in order to ensure the stability of tracking, the number of particles must be large enough, which leads to an increase in the amount of calculation. Meanshift, as one of the typical representatives of matching tracking methods, has been widely valued for its advantages of small amount of calculation, but it cannot guarantee the global optimum during the tracking process, and it is easy to fall into local optimum. Contents of the invention [0003] The present invention aims to overcome the defective that prior art exists, and the present invention adopts following technical scheme: [0004] The invention provides a real-time color target tracking method. The real-time color target tracking method i...

AI Technical Summary

Problems solved by technology

[0002] Particle filter has developed rapidly in the field of target tracking and achieved good results, but in order to ensure the stability of tracking, the number of particles must be large enough, which leads to an increase in the amount of calculation

Meanshift, as one of the typical representatives of matching tracking methods, has been widely valued for its advantages of small amount of calculation, but it cannot guarantee the global optimum during the tracking process, and it is easy to fall into local optimum.

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