一种改进的运动目标抗遮挡跟踪算法

为解决运动目标在遮挡情况下的跟踪问题,提出一种基于目标运动预测与自适应多子块模板匹配相结合的抗遮挡跟踪算法.该算法建立了多子块模板匹配相关算法中遮挡情况的判定、子块模板匹配及自适应更新等准则,采用卡尔曼滤波模型预测目标在遮挡时的运动轨迹,并利用一种基于目标速度矢量的模板定位规则实现目标在遮挡结束后的接力跟踪.将该算法应用于存在多种遮挡情况下的实际视频中进行测试,实验结果表明:该算法不仅能够实现在部分遮挡情况下的目标跟踪,而且能在严重遮挡、甚至完全遮挡情况下对刚体和非刚体目标进行稳定有效地跟踪,保持目标运动轨迹的可靠性和完整性.

Improved algorithm of tracking moving objects under occlusions

To better settle the problem of tracking objects under occlusions, an improved anti-occlusion tracking algorithm was proposed, based on the combination of motion prediction and adaptive multi-block template matching. The algorithm constituted the principle of detecting occlusions and the method of updating and matching multi-block templates. Kalman filter was applied to predict the object’s trajectory under occlusions. A template location rule based on the object’s velocity was adopted to re-track object after occlusion. Tracking experiments under various conditions of occlusion indicates that this algorithm succeeds to track rigid and non-rigid objects when heavily, even completely occluded, by static background. Moreover, the reliability and integrity of objects’ moving trajectories are guaranteed.