电信科学 ›› 2010, Vol. 26 ›› Issue (5): 110-113.doi: 10.3969/j.issn.1000-0801.2010.05.032

• 研究与开发 • 上一篇    下一篇

基于隐马尔可夫Particle Filter实现突变运动智能监控研究

朱敏,苏博   

  1. 贵州大学职业技术师范学院 贵阳 550003
  • 出版日期:2010-05-15 发布日期:2010-05-15
  • 基金资助:
    教育部“十一五”重点规划资助项目

Research of HMM Particle Filter Mutation Sports Intelligent Monitoring

Min Zhu,Bo Su   

  1. Guizhou University Vocational Education College，Guiyang 550003，China
  • Online:2010-05-15 Published:2010-05-15

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摘要：

目前智能监控系统较为常用的是粒子滤波（particle filter）算法，粒子滤波算法在非线性、非高斯滤波问题上有着独特的优势，然而，随着监控系统对目标追踪效果的要求不断提高，算法不断进行更新，普通的粒子滤波算法已经不能够满足监控系统日益增长的需求。对于较复杂的场景，如面积背景突变运动已经不能够很好地进行追踪监控。本文针对这个问题，利用隐马尔可夫模型（HMM）对粒子跟踪算法进行了多方面的优化，实现了对目标的智能监控。

关键词: 粒子滤波, 隐马尔可夫模型, 突变运动, 智能监控

Abstract:

Particle filter algorithm is currently used in intelligent monitoring system. It has unique advantages in non-linear， non-Gaussian filtering. However，with demands increasing to track target in the monitoring system，the algorithms continually are updated，ordinary particle filter monitoring system is no longer able to meet the growing demand. For more complex scenes，for example，an area of the background mutation movement can’t be primely monitored. Aim at this probelm，the paper used HMM particle filter to track，and realized the target of intelligent monitoring.

Key words: particle filter, HMM, mutation movement, intelligent monitoring

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