首页 /研究 /Real time object tracking on video image sequence using particle swarm optimization
SWARM

Real time object tracking on video image sequence using particle swarm optimization

Tomoaki Kobayashi, Keita Nakagawa, Joe Imae, Guisheng Zhai

发表年份
2007
引用次数
24

摘要

Real time object tracking method on video sequence is important technology for robot vision, security sys- tems 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.

关键词

Particle swarm optimizationComputer visionVideo trackingComputer scienceArtificial intelligenceSequence (biology)Object (grammar)Tracking (education)Swarm behaviourAlgorithm

相关论文

查看 SWARM 分类全部论文