球粒子滤波视频跟踪算法

Ball Particle Filter Algorithm for Visual Tracking

粒子退化现象是制约粒子滤波器性能的一个重要因素.为提高粒子采样质量和视频跟踪算法的精度,文中提出球粒子滤波视觉跟踪算法.将球状采样方式引入到粒子更新过程中较好地保证状态空间中粒子的有效性.与传统粒子滤波算法相比,这种采样方式能利用少量粒子实现分布多样性的同时,有效克服粒子退化现象.小球迭代运动可使粒子集朝较大后验概率分布区域移动.球粒子滤波算法不依赖系统状态模型特性可理想实现运动状态不规则的机动目标跟踪.实验结果表明,该算法有效提高粒子利用率,具有较好的跟踪精度.

Particle degeneration is a key issue which influences the performance of a particle filter. To improve the quality of particle sampling and the accuracy of visual tracking, a ball particle filter algorithm for visual tracking is proposed. Ball sampling mode guarantees the valid particles in state-space. Compared to the conventional particle filter, the proposed method uses much fewer particles to ameliorate the diversity of distribution, and overcomes the degeneration problem effectively. By iterative motion of ball, particles are moved towards the regions with larger values of posterior density function. Ball particle filter without depending on state-mode can track the maneuver object with irregular movement. The simulation results show that the proposed method improves the efficiency of particles and achieves fine tracking precision.