一种基于遗传算法和卡尔曼滤波的运动目标跟踪方法

提出了一种基于遗传算法和卡尔曼滤波的运动目标跟踪方法。该方法利用卡尔曼滤波预测目标中心在下一帧图像中可能出现的位置，以该位置为中心，建立候选的目标搜索区域。以跟踪目标的灰度统计特征为模板，以Bhattacharyya系数来度量目标模板与候选目标区域的相似性，并以此相似性作为遗传算法适应度函数，以候选目标中心坐标作为参数编码，利用遗传算法进行匹配搜索，最终获得最佳候选区域中心位置，同时以该位置作为观测值，进行下一帧预测。实验结果表明，该方法具有较好的实时性和鲁棒性。

Tracking of moving object based on genetic algorithm and Kalman filter

A real-time tracking of moving object method based on Genetic Algorithm(GA)and Kalman filter was proposed.The possible position of moving target center in the next frame image was predicted by Kalman filter,and a search region of target was generated around the center position.Genetic Algorithms(GA)was utilized to search the best position in the region.The GA fitness function was Bhattacharyya coefficient between the gray features of the target template and the candidate area's,and the parameter code was the coordinates of candidate center position.Finally,the best position was used as an observed value for next prediction.The experimental results show that the method is effective and robust.