利用增广拉格朗日乘子的鲁棒跟踪算子

针对视频目标鲁棒跟踪问题,提出了一种基于稀疏表示的生成式算法。首先提取特征构建目标和背景模板,并利用随机抽样获得足够多的候选目标状态;然后利用多任务反向稀疏表示算法得到稀疏系数矢量构造相似度测量图,这里引入了增广拉格朗日乘子(ALM)算法解决L₁-min难题;最后从相似度图中使用加性池运算提取判别信息选择与目标模板相似度最高并与背景模板相似度最小的候选目标状态作为跟踪结果,该算法是在贝叶斯滤波框架下实现的。为了适应跟踪过程中目标外观由于光照变化、遮挡、复杂背景以及运动模糊等场景引起的变化,制定了简单却有效的更新机制,对目标和背景模板进行更新。对仿真结果的定性和定量评估均表明与其他跟踪算法相比,所提算法的跟踪准确性和稳定性有了一定的提高,能有效地解决光照和尺度变化、遮挡、复杂背景等场景的跟踪难题。

Robust tracking operator using augmented Lagrange multiplier

Focusing on the problem of robust video object tracking, a robust generative algorithm based on sparse representation was proposed. Firstly, object and background templates were constructed by extracting the image features, and sufficient candidates were acquired by using random sampling method at each frame. Secondly, the sparse coefficient vector was got to structure the similarity map by an innovative optimization formulation named multitask reverse sparse representation formulation, which searched multiple subsets from the whole candidate set to simultaneously reconstruct multiple templates with minimum error. Here a customized Augmented Lagrange Multiplier (ALM) method was derived for solving the L₁-min problem within several iterations. Finally, the additive pooling was proposed to extract discriminative information in the similarity map for effectively selecting the best candidate which the most similar to the object template and was most different to the background template to be the tracking result, and the tracking was implemented within the Bayesian filtering framework. Moreover, a simple but effective update mechanism was made to update object and background templates so as to handle the object appearance variation caused by illumination change, occlusion, background clutter and motion blur. Compared with the other tracking algorithms, both qualitative and quantitative evaluations on a variety of challenging sequences demonstrate that the tracking accuracy and stability of the proposed algorithm has improved and the proposed algorithm can effectively solve target tracking problem in these scenes of illumination and scale changing, occlusion, complex background, and so on.