基于积分协方差矩阵的粒子滤波目标跟踪

摘要

仅利用单一特征的目标跟踪难以克服光照和目标形变等外部条件变化，给出一种基于协方差区域描述子的粒子滤波，协方差描述子可融合目标区域内的多种特征处理复杂背景下的目标跟踪问题，提高跟踪的鲁棒性；针对粒子滤波计算量大的问题，引入积分协方差矩阵计算，提高跟踪的实时性，对比实验表明新的跟踪算法比仅用单一特征跟踪鲁棒性更高，处理速度更快。%The target tracking only using single feature is difficult to overcome the influence of external conditions such as the illumination and target deformation etc.,a particle filter target tracking algorithm based on the covariance region descriptor is proposed.The covariance descriptor can fuse different features of the target region to handle target track-ing under complex background.And then,the tracking robustness is improved.Moreover,aiming at the problem that calculation of particle filter is large,the integral covariance matrix computation is introduced to Bayesian tracking framework,which makes the tracking process realtime.The comparative experiments show that the proposed algorithm is more robust and faster than the single feature tracking.