Multi-Objects Tracking Based on HPSO-TVAC Algorithm
| Autor: | Jung-Kuei Chang, 張榮貴 |
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| Rok vydání: | 2014 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 102 In order to improve the tracking speed and solve the shadowing problem, this paper trace objects by “Self-Organizing Hierarchical Particle Swarm Optimizer with Time-Varying Acceleration Coefficients (HPSO-TVAC)”, which improved from PSO algorithm. We use the relationship between the members of the groups to make whole groups go along toward the way of better goals by HPSO-TVAC algorithm, and we also uses “adaptive searching window”. Then the searching window will zoom in or out which depends on global best fitness. While we can find the targets, we will make the searching window contains small, but while we cannot find the targets, we will let the searching window bigger to find the targets. The improved seeded region growing method, which we mainly improved the quantity of seeds, is presented in this study. We reduce quantity of seeds to increase the efficiency, and it can let us distinguish between different targets. In this study, we use background subtraction to distinguish background and moving objects, and we also use improved seeded region growing method to distinguish different targets. Then we use color histograms to build target models, and trace every targets by HPSO-TVAC algorithm. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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