改进PF算法对红外图像中瞳孔的跟踪  

IR Pupil Tracking Based on Optimized Particle Filter

作　　者：赵三元[1] 沈庭芝[1] 林健文[1] 胡宇[1] 田卉[1] 

机构地区：[1]北京理工大学信息与电子学院,北京100081

出　　处：《北京理工大学学报》2009年第11期994-997,共4页Transactions of Beijing Institute of Technology

基　　金：国家自然科学基金资助项目(60772066)

摘　　要：提出一种基于粒子滤波的红外目标跟踪的新算法.用该算法对采样粒子进行优化,改进了重采样环节,在不影响跟踪准确率的条件下,提高了算法的速度.实验结果表明,将此算法运用到瞳孔跟踪中,跟踪比较准确有效.同时,将Hough变换应用到了瞳孔边缘的定位领域中,此算法有效改进了红外图像中眼睛瞳孔的跟踪效果.Abstract： Presents a particle filter-based algorithm for IR target-tracking. In this algorithm, sampling particles are optimized and selected, and the re-sampling phase is improved. It solves the problems of massive computation in traditional particle filter. And this method is adopted in tracking pupil, which has better precision and higher efficiency. The paper also applied Hough transform to locate the edge of pupil and achieved very good results.

关 键 词：瞳孔定位 粒子滤波 粒子重采样 

分 类 号：TN247[电子电信—物理电子学]