基于切分模板的实时跟踪算法

相关匹配算法是一种经典的匹配算法 ,通过计算模板图像和待匹配图像的互相关值来确定匹配的程度 ,具有很高的准确性和适应性 ,在目标跟踪中得到了广泛应用。但是相关匹配算法计算耗时过于庞大 ,难以达到实时要求 ,并且当目标在模板中所占比例很小时 ,很难确定模板的准确位置 ,使得此算法在实时目标跟踪中难以得到应用。文中在相关匹配的基础上提出了一种基于切分模板的实时跟踪算法。匹配的模板被分为几个部分 ,每个部分均有不同的加权值 ,最后的相关匹配度为各部分匹配度的加权和。算法中还设置了一个不是实时更新的加权模板 ,以提高算法的抗干扰能力 ,并采用金字塔搜索算法进行加速。实验结果显示 ,此算法有效地克服了相关匹配算法的缺点 ,具有较好的匹配精度和实时性

Real Time Tracking Algorithm Based on Adaptive Model

The correlation matching algorithm determines the matching model and grabbed image by calculating their correlation values. Because the algorithm has high precision and strong adaptability and is robust to linear change of gray scale, it is widely used in projects as a classic matching algorithm. But correlation match computing is very time consuming and is difficult to satisfy the real time requirement. Besides, when target is only a small part in model, it is hard to confirm the model position. In this paper, a cut model based real time tracking algorithm is introduced. The model is segmented into several parts and there is a different weight coefficient in every part. The matching score is the weighted sum of the matching scores of each part. An weighted model is set in algorithm in order to resist disturbing and it is accelerated by pyramid algorithm. Results show that, when target is very small in the model, the tracking algorithm has better matching precision and real time.