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使用Camshift 算法做目标跟踪,当目标被遮挡后,用Bp神经网络+Kalman联合预测

C++ 98.67% C 1.33%

bpkalmanfusiontracking's Introduction


BpKalmanFusionTracking

BP神经网络_Kalman滤波联合预测跟踪


平台工具集:

  • Windows7 64位
  • Visual Studio 2017
  • OpenCV 3.4.1

项目简介:

  1. 读取本地视频,进行基本Camshift跟踪,同时建立目标直方图模型和搜索窗的直方图模型,然后用巴氏距离判断相似性,当巴氏距离(dSimilarity)小于阈值(Threshold)时,判定目标被遮挡,然后使用BP神经网络+Kalman滤波联合预测,然后用预测值代替其真实值进行跟踪。

  2. 在神经网络模型中,构建大小为6的容器,每次训练预测均使用前六个时刻的值。

  3. 卡尔曼滤波器的状态方程为三阶,即变加速运动。

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