基于光流和Snake算法的运动目标检测

Detection of Moving Object Using Adaptive Optical Flow and Snake Algorithm

提出一种帧间双差分法、自适应光流、snake算法相结合的运动目标检测方法。通过帧间双差分法提取运动区域,针对运动区域进行光流计算,对光流计算结果进行C-均值聚类,最后用聚类结果作为snake算法的初始值,通过贪婪算法对活动轮廓进行收缩,把运动目标的轮廓精确的包围起来。由运动目标真实图像序列的实验结果充分证明了算法的优良性能,可以有效地从复杂自然场景的图像序列中检测出完整的运动目标。

We proposed a method on detection of moving object using symmetrical DFD,adaptive optical flow and snake algorithm. First get the motion area of the moving object by symmetrical DFD,and estimate the optical flow of this area; then employ the C-Mean cluster algorithm to cluster the result of the optical flow; finally,the initial position of Snake is set automatically from the clus-ter result. The converged contour of the final object is got by using greedy algorithm. Experimental results show that the algorithm can quickly and exactly detect the multiple moving objects from natural images with complex backgrounds.