kalman filter tracking
2016-08-23
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Set up a Kalman filter with 4 dynamic parameters and 2 measurement parameters (no control), where my measurement is: 2D location of object, and dynamic is: 2D location and 2D velocity.
First predict, to update the internal statePre variable
Mat prediction = KF.predict();
Point predictPt(prediction.at<float>(0),prediction.at<float>(1));
// Get mouse point
measurement(0) = mouse_info.x;
measurement(1) = mouse_info.y;
c++
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卡尔曼
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