Real time Face Tracking by Genetic Particle Filter

摘要：

There are a great variety of human faces tracking methods based on particle filter. However, most tracking algorithms, so far, are unable to meet the demands for both precise and fast tracking.A real-time algorithm, based on genetic particle filter (GPF) for human faces tracking is presented in this paper. The crossover and mutation operations in evolutionary computation are introduced into PF to make samples move towards regions with large value of posterior density function (PDF). Experiments results Show that GPF presents improvements over the PF techniques regarding to robustness, accuracy and flexibility in dynamic environment.Mean while, gPF,which needs fewer samples,improve the speed of tracking.

关键词： Face Tracking Genetic Algorithm Particle Filter Posterior Density

作者: LIU Yanli ZHANG Heng

作者单位: School of Information Engineering,East China Jiaotong University,Nangchang 330013,China

会议类型: 国际会议

会议名称: 2009年中国控制与决策会议(2009 Chinese Control and Decision Conference)

会议地点: 广西桂林

会议语种:英文

页码: 4393-4398

在线出版日期: 2009-06-17（万方平台首次上网日期，不代表论文的发表时间）