复杂情形下目标跟踪的自适应粒子滤波算法

该文提出一种自适应粒子滤波算法。首先建立目标的颜色模型，提出基于加权颜色分布图的目标颜色模型。采用该模型计算目标模板与粒子区域的相似程度，以此作为对目标物体定位的依据，使目标定位更加合理有效；进而在滤波过程中，针对粒子退化问题，提出基于mean-shift迭代的粒子重抽样方法，形成对抽样粒子集的自适应调节，提高了粒子质量，有效降低了粒子数量。最后，进行了对大机动快速运动的小目标和被严重遮挡目标的跟踪实验，结果表明该算法具有较强的鲁棒性。

Visual Target Tracking Based on the Adaptive Particle Filter in the Complex Situation

This paper presents an adaptive particle filtering algorithm for image tracking based on weighted color probability contribution. First, a weighted color contribution graph is proposed. Taking use of the graph, similarity between target template and particles area is calculated, that makes the target located more reasonable and efficient. During the filtering, aiming at particles degeneration, a resampling method is proposed, forming adaptive adjustment to sampled particle-set. This promotes quality of particle and reduces its quantity while cost of calculation is reduced greatly. Experiment result shows, for some complex tracking conditions such as overall occultation and object tracking with fast moving and great maneuverability, the proposed algorithm has a better robust.