OPENCV & C++ TUTORIALS - 149 | Kalman Filter Post State | statePost()

Kalman Filter is used in many engineering systems in the world. In this video we focused on the Computer vision side. This video contains a simple simulation example to understand the post state(statePost) of kalman filter transition matrix in Object tracking. In Computer vision we use Kalman filter to estimate the next destination points of a motion by giving the observed data into it as input.

🌠 I will continue to this tutorial series with this plan : https://docs.opencv.org/4.3.0/modules.html

🌠Kalman Filter class: https://docs.opencv.org/4.3.0/dd/d6a/classcv_1_1KalmanFilter.html

🌠 You may want to watch also: https://www.youtube.com/watch?v=gbGPBE26Fkc

🌠 Stackoverflow: https://stackoverflow.com/users/11048887/yunus-temurlenk?tab=profile

🌠 Github: https://github.com/yunus-temurlenk?tab=repositories

🌠 Twitter: https://twitter.com/code_enjoy

🌠Hashnode: https://yunustemurlenk.hashnode.dev/

▬ Contents of this video ▬▬▬▬▬▬▬▬▬▬

0:00 - Introduction
0:50 - Coding part & Results

If you see any mistake and any advice please comment. Thanks for watching...

#opencv, #statePost, #KalmanFilter

Видео OPENCV & C++ TUTORIALS - 149 | Kalman Filter Post State | statePost() канала Computer Vision Lab