融合背景信息的改进粒子滤波跟踪算法

为消除传统粒子滤波算法在跟踪目标受到相似背景干扰和遮挡时,容易造成跟踪误差增大或跟踪失效的影响,提出融合背景信息的改进粒子滤波跟踪算法.利用对数似然函数将背景信息融入目标模型,并将目标分为多个子区域增强目标模型的可靠性,有效克服了相似背景对目标的干扰;然后存储一定时间的历史轨迹信息,通过最小二乘法进行拟合并预测下一帧目标出现的位置,有效克服了遮挡对跟踪的影响.实验结果表明,该算法比传统的粒子滤波算法具有更强的抗背景干扰能力,在遮挡情况下也有更好的跟踪精度.

An Improved Particle Filter Tracking Algorithm with Background Information Fusion

The traditional particle filter tracking algorithm usually leads to tracking error or failure,when the target is interfered by the similar background or blocked by the other object.To eliminate these effects,an improved method was proposed.To overcome the background interference,the logarithm likelihood function was used to fuse the background information into the target model,and the target was divided into multiple sub-regions to fuse the spatial information into the target model,which increase the model ...