基于SIFT特征匹配的CamShift运动目标跟踪算法

针对复杂背景下采用一般CamShift算法跟踪目标容易失败,提出将SIFT(Scale Invariant Feature Transform)特征点匹配融入到CamShift算法。该算法利用SIFT特征对尺度和方向无关特性实现连续图像序列的精准匹配,具有对尺度缩放、目标旋转以及亮度变化保持不变性的优点,不仅弥补了一般CamShift算法只以颜色为关键信息的不足,而且可将目标跟踪窗口形心和质心间的位移稳定在设定阈值内。最后通过对比性实验来验证该算法的有效性和稳定性。实验结果表明,该算法能够对复杂背景下的光照突变、缩放和旋转运动目标实现实时稳定跟踪。

CamShift Moving Object Tracking Algorithm Based on SIFT Feature Points Matching

A new algorithm integrating SIFT feature points matching into CamShift algorithm was proposed,aiming at tracking object which is prone to failure caused by using general CamShift algorithm under complex backgrounds.The algorithm uses the SIFT feature to realize precise matching of the continuous image sequence which has nothing to do with scale and direction.And it is partially invariant to object scaling,translation and illumination change.Not only it compensates for the lack of taking color as key information of the general CamShift,but also the displacement between the centroid and the center of mass of object tracking window is stable within the threshold.Finally,the effectiveness and stability of the algorithm were verified via comparative experiments.The experimental results show that the new algorithm can achieve stable tracking object against illumination mutations,scaling and rotation under the complex backgrounds.