Particle Filter Target Tracking Algorithm Based on Dynamic Niche Genetic Algorithm

Weicheng XIE  Junxu WEI  Zhichao CHEN  Tianqian LI  

IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E100-A   No.6   pp.1325-1332
Publication Date: 2017/06/01
Online ISSN: 1745-1337
Type of Manuscript: PAPER
Category: Vision
dynamic niche,  particle filter,  feature fusion,  sample impoverishment,  target tracking,  

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Particle filter algorithm is an important algorithm in the field of target tracking. however, this algorithm faces the problem of sample impoverishment which is caused by the introduction of re-sampling and easily affected by illumination variation. This problem seriously affects the tracking performance of a particle filter algorithm. To solve this problem, we introduce a particle filter target tracking algorithm based on a dynamic niche genetic algorithm. The application of this dynamic niche genetic algorithm to re-sampling ensures particle diversity and dynamically fuses the color and profile features of the target in order to increase the algorithm accuracy under the illumination variation. According to the test results, the proposed algorithm accurately tracks the target, significantly increases the number of particles, enhances the particle diversity, and exhibits better robustness and better accuracy.