提出一种多特征融合和带宽自适应均值偏移跟踪算法。基于M-估计器建立位置和带宽关于完整参数型带宽矩阵的迭代更新公式。分析权值图像的本质，基于灰度和局部标准差建立融合权值图像。通过先前目标模板模型和确定的目标模型的平均值生成当前目标模板模型。在位置向量的迭代公式中，采用扩大的带宽矩阵，确保定位精度。为防止由于背景杂波导致带宽膨胀或者由于目标自我相似导致带宽收缩，引入规范准则。跟踪的视觉结果和评估尺度表明，提出的跟踪算法相比于另外三种尺度自适应均值偏跟踪算法，具有最好的性能。

A multiple features fusion and bandwidth adaptive mean shift tracking algorithm had been proposed. The iterative solution expressions of location and bandwidth had been established with fully parameterized bandwidth matrix based on M-estimator. The fused weight image had been produced with intensity and local standard deviation. The target template model had been generated by the combination of previous target template model and the mean value of the determined target models in the previous frames. An enlarged bandwidth matrix had been employed in the iterative solution of location vector to ensure location accuracy. To prevent the bandwidth from exploding in the presence of background clutter or imploding on self-similar target, regularization terms had been introduced. The visual results and evaluation measures show that the proposed tracking algorithm has the best performance compared with other three scale adaptive mean shift tracking algorithms.