支持向量机和AdaBoost目标跟踪新方法

New Target Tracking Algorithm Based on Support Vector Machines and AdaBoost

在目标跟踪领域,目标检测对跟踪的效果起决定性作用,提出一种用支持向量机进行目标跟踪的方法。采用AdaBoost算法选择最具有代表性的Harr特征,将选择出来的特征作为支持向量机训练器的输入数据来训练目标检测分类器。为了加速检测速度,使用了层叠加速检测算法。实验结果表明,该算法不但提高了识别的正确率,而且大大提高了检测速度。

It is very important to target detecting in the field of target tracking field. A kind of detection algorithm using support vector machine is proposed in this paper. It selects representative Hart characters using AdaBoost method and taking it as input data of support vector machines. In order to accelerate detecting speed, the cascade method is also been used. The experiment result shows that this algorithm improves not only the tracking precision but detecting speed.