基于分块运动估计的对象跟踪方法

针对摄像机运动和场景光照突变的情况,提出了一种基于分块运动估计的对象跟踪算法。首先,对图像进行分块角点匹配,得到各块运动参数,然后对各块进行分块运动补偿和光照补偿;对补偿后的图像进行相邻帧差分得到目标的近似质心位置;跟踪过程则融合运动目标加权颜色直方图和梯度直方图作为目标特征,以所得质心为初始搜索点,采用螺旋搜索算法,进行目标模板和候选目标相似性检测,搜索最佳匹配点得到目标对象在当前帧的准确位置。实验结果表明,该算法能够有效克服光照剧烈变化,在动态背景下能达到对对象的准确跟踪。

Object Tracking Method Based on Block Motion Estimation

The author puts forward one object tracking method based on block motion estimation which can overcome sudden light change and obtain good tracking performance in dynamic background. Firstly,block motion compensation and light compensation are processed according to the parameters acquired by block Harris corner match. Then based on the multi-feature fusione,combining the color histogram and HOG as the object feature,the algorithm will search for the candidate,with the math point calculated with inter-frame difference as the original searching point,which matches the model in the best way. The experiments show that this algorithm can realize accurate and real time tracking in dynamic background and can overcome sudden light change as well.