基于目标质心的Meanshift跟踪算法

A Meanshift Tracking Algorithm Based on Centroid

运动目标跟踪涉及到计算机图像处理、视频图像处理、模式识别以及人工智能等诸多领域,是一门交叉性很强的学科。因此,研究一种实时性、鲁棒性好的运动目标跟踪方法依然是该领域面临的一个巨大挑战。快速运动目标跟踪技术是当今目标跟踪领域的难点之一。均值漂移算法在目标跟踪过程中没有利用目标的运动方向和速度信息,这就导致了无法准确跟踪快速目标。文中提出了一种基于质心算法的Meanshift跟踪模型算法。初始位置采用运动目标质心,并在质心位置处采用Meanshift迭代,以巴氏系数判断当前目标和参考目标的匹配程度。实验分析,该算法可实现快速、有效跟踪目标。

Moving target tracking is a highly cross-disciplinary, which involves many fields, such as computer image processing, video image processing, pattern recognition,artificial intelligence and so on. Therefore, the research of real-time and robustness is still a great challenge in thc field of object tracking. Fast motion target tracking is one of the most difficulties in the field. Meanshift algorithm doesn＇ t use the target＇ s motion direction and speed information in process of target tracking. So it brings about failures in fast motion target tracking. An algorithm combined center of gravity with Meanshift algorithm is proposed in this paper. At first, use the centroid as initial position;And then Meanshift iteration is done in the location of the centroid;And the Bhattacharyya＇ s coefficient is applied to judge the matching degree between the current target and reference target. Experimental results show that the new algorithm can help achieve fast and effective object tracking.