Documentation
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Overview ¶
What it does:
This example implements the kalman filter example from:
https://docs.opencv.org/4.6.0/de/d70/samples_2cpp_2kalman_8cpp-example.html#_a7
Tracking of rotating point. Point moves in a circle and is characterized by a 1D state.
state_k+1 = state_k + speed + process_noise N(0, 1e-5)
The speed is constant. Both state and measurements vectors are 1D (a point angle). Measurement is the real state + gaussian noise N(0, 1e-1). The real and the measured points are connected with red line segment. The real and the estimated points are connected with yellow line segment. The real and the corrected estimated points are connected with green line segment.
If Kalman filter works correctly, the yellow segment should be shorter than the red one andthe green segment should be shorter than the yellow one).
Pressing any key (except ESC) will reset the tracking. Pressing ESC will stop the program.
How to run:
go run ./cmd/kalman-filter/main.go
Source Files