科研之友
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摘要
The particle swarms algorithm is a new evolutionary algorithm, its ideal is suitable for video tracking, but since the tracing window is considered as particle in the process of video tracking, so this particle has three-dimensional characteristic vectors i. e. the vertical and lateral coordinate of the central point, the radius of window, the calculated quantity is too large to meet the real time requirement in video tracking. The changes of object scale and position within the kernel will not impact localization accuracy of particle swarms based on tracking algorithm using the Bhattacharyya coefficient as criterion function. According to this analysis, a multiple particle swarms algorithm of video tracking is presented, the ideal is that several particle swarms are used in tracking process, the particle radius between particle swarms is different, but the particle radius in the same swarm is the same, so that there is only two-dimensional motion while every particle swarm are searching its optimum central point, the factor of variation (mutation) is introduced in the process in order to let one particle swarm can be under the influence of the other particle swarms. After each particle swarm convergences to its optimum central point according to criterion function with Bhattacharyya coefficient, the one-dimensional particle swarm calculation for each radium can be completed, it can be seen that the three-dimensional particle swarms calculation is divided into one two-dimensional and one one-dimensional warms calculations in the new method. At last the results of particle swarms calculation are compared and the optimum particle is obtained as the searching result. The simulation results show that the presented multiple particle swarms algorithm of video tracking is able to apply in real time, and the tracking performance is superior to conventional algorithms.
- 出版日期2010
- 单位北京理工大学
