Kalman filter for image

Basic kalman filter for image object tracking, noise remove.

• 2D optimization code (replace matrix inverse --> matrix multiplication)
• pre&post process interface and example
• Only depends on "numpy"

keypoints stablizing & tracking

🤘 **rock 'n' roll** 🤘

Requirements

• python 3
• numpy
• pandas
• opencv-contrib-python

Usage

First, install libs

pip install opencv-contrib-python
pip install numpy
pip install pandas

Just run!

python main.py

---

Description

17 human pose keypoints (coco style)

matrix

x = [x_postition, x_velocity, y_position, y_velocity]

    self.dt = dt                            # time interval
    self.A = np.array([                     # system matrix
        [1, dt, 0,  0],
        [0,  1, 0,  0],
        [0,  0, 1, dt],
        [0,  0, 0,  1],
    ], dtype=np.float)
    self.H = np.array([                     # system matrix
        [1, 0, 0, 0],
        [0, 0, 1, 0]
    ])
    self.Q = 0.9*np.eye(4, dtype=np.float)  # system error matrix
    self.R = np.array([                     # measurement error matrix
        [100, 0],
        [0, 100]
    ], dtype=np.float)