Real time object tracking on video image sequence using particle swarm optimization
Real time object tracking on video image sequence using particle swarm optimization
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DOI：
10.1109/iccas.2007.4406632
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发表时间：
2007-12
期刊：
影响因子：
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通讯作者：
Tomoaki Kobayashi;Keita Nakagawa;J. Imae;G. Zhai
中科院分区：
文献类型：
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作者：
Tomoaki Kobayashi;Keita Nakagawa;J. Imae;G. Zhai
视频序列上的真实的实时目标跟踪方法是机器人视觉、利用视觉信息的安全系统等领域的重要技术。本文提出了一种基于粒子群优化（PSO）的目标跟踪算法。在PSO算法中，属于群体的每个粒子（个体）有效地利用整个群体的信息搜索最优解。在本文中，我们提出了一种有效的目标跟踪技术，在广泛的搜索范围内应用粒子群算法搜索视频图像序列中的运动目标。我们通过一些仿真和实验证明了我们的方法的有效性和实用性。
Real time object tracking method on video sequence is important technology for robot vision, security systems using visual information, etc. We propose an object tracking algorithm using particle swarm optimization (PSO) technique, which is an optimization method inspired by swarm behaviors. In PSO algorithm, each particle (individual) belonging to the swarm searches optimal solution efficiently using entire swarm information. In this paper, we propose an effective object tracking technique in a wide expanse of search range by applying PSO for searching a moving object in the video image sequence. We demonstrate the effectiveness and practical utility of our method through some simulations and experiments.