基于背景差分和粒子滤波的运动目标跟踪算法

A Moving Target Tracking Algorithm Based on Background Subtraction and Particle Filter

针对粒子滤波算法在复杂环境下粒子数量显著增加导致跟踪实时性下降的问题,提出一种将背景差分引入到粒子滤波算法中的新算法.利用背景差分对图像处理后得到检测结果,将分布在已被检测为前景像素点上的粒子定义为重要性粒子,增大了其权值.实验结果表明,该算法能使用较少的粒子实现较好的跟踪,提高了跟踪的实时性.

To solve the problem of low real-time tracking caused by the increased particles in a complex environment based on the algorithm of particle filter,the author introduced the background subtraction into the particle filter to propose a new algorithm.After getting the detection result from the image background subtraction,the particle that has been detected to be on foreground pixel is defined as ＂the important particle＂,whose weight grows.Experiments show that the proposed algorithm can achieve better tracking based on fewer particles,and it also improves the real-time tracking.