基于双矩形框标定的改进TLD算法

Improved TLD Algorithm Based on Region Marking of Double Bounding Boxes

鉴于基于单个矩形框标定的Tracking-Learning-Detection(TLD)算法无法兼顾跟踪目标的"重点性"和"完整性",提出了一种基于双矩形框标定的改进算法。在标定整个目标区域的矩形框的基础上,算法在目标变化相对稳定的区域标定另一个矩形框,以指示跟踪的重点区域。在提取跟踪点时,采用分配权重的方法使重点区域产生更多的跟踪点,从而提高算法对局部变化的适应能力。实验表明,改进后的算法在跟踪局部保持稳定而其余部分有所变化的目标上有较高的性能提升;而对于不存在稳定局部区域的目标,跟踪效果没有明显改善。

Considering that the Tracking-Learning-Detection （TLD） framework can hardly balance the tracking of the whole and the interest, by using region-marking method of single bounding box, this paper proposed an improved algorithm introducing a region-marking method of double bounding boxes. With one bounding box labeling the whole object, the algorithm draws another bounding box over the stable area of image to indicate the interested part. While extracting the trace points, the weighting approach is adopted to produce more points in interested area,which improves TLD＇s adaptability to local variance. Experimental results show that the improved algorithm has good performance in tracking the object when a fixed part keeps stable but the rest varies. For the object not containing the stable local area, the effects are not so obvious.