基于最优特征选择的车辆跟踪方法

Vehicle Tracking Method Based on Optimal Feature Selection

针对智能交通系统的车辆跟踪问题,提出基于最优特征选择的车辆跟踪方法。综合颜色、纹理和形状特征确定特征集合,采用线性鉴别分析方法从特征集合中选取最优特征,使用Mean Shift算法在最优特征下预测目标位置,根据目标匹配结果确定车辆的运行轨迹,利用特征平滑方法更新特征模型。实验结果表明,该方法适用于不同的公路监控场景,能够准确、有效地跟踪运动目标。

Aiming at vehicle tracking problem of intelligent transportation system,this paper proposes a vehicle tracking method based on optimal feature selection.The method integrates color,texture and shape characteristics to create a feature set,and applies Linear Discriminate Analysis（LDA） method to select optimal characteristics as input features of the Mean Shift algorithm,predicts of the target location,and determines the vehicle＇s trajectory by matching targets.Feature model is updated by smooth method.Experimental results show that this method can track vehicle accurately and effectively in different highway monitor scenarios.