基于Camshift和SIFT线性融合的目标跟踪算法研究

Camshift算法是对MeanShift算法的改进，它可以解决目标尺度缩放、持续跟踪等问题。但是当目标颜色与背景颜色接近或者目标遇到旋转问题时，Camshift算法容易失效。而SIFT算子对旋转、亮度变化保持不变性，对颜色相近也保持一定的稳定性，所以本文提出一种Camshift与SIFT算子线性融合的目标跟踪算法。首先利用Camshift算法来对目标进行初步的跟踪，得到跟踪区域，再利用SIFT特征向量来匹配目标区域与跟踪区域，得到SIFT的匹配和校正结果，再将两种算法的结果进行线性融合，得到最终的跟踪结果。实验结果表明，本文提出的方法可以有效地解决跟踪过程中出现的旋转、颜色相近等问题。

Object Tracking algorithm Based on the Linear Fusion of Camshift and SIFT

Camshift algorithm is an improvement of the MeanShift algorithm, which can solve the scale change and continuous tracking. But when the color of the targets are similar to the color of background, or the targets rotate, Camshift algorithm may fail. Meanwhile, SIFT operator not only keep invariant to rotation and illumination, but also keep the stability of similar color. So this paper proposes a target tracking algorithm that fuse the Camshift and SIFT operator. Firstly, Camshift algorithm is used to track the moving target preliminary and get the tracking area. Secondly, using the SIFT feature vector to match the target area and tracking area, so the SIFT matching and correction results are obtained. Lastly, the target tracking results are linear fusion of the two algorithm, which get the ultimate results. Experimental results show that the proposed method can effectively solve the occlusion and the rotation in the tracking.