Hello Viabyte! In this article, we will explore the Kalman filter algorithm and how to implement it using OpenCV and Python. We will also provide a step-by-step guide on how to use Kalman filter in an example code.
What is Kalman Filter?
Kalman filter is a mathematical algorithm used to estimate a state of a system based on observations. It is a recursive algorithm that estimates the state of a system over time. It is widely used in various fields such as engineering, physics, and computer science.
Kalman filter is useful when the observations are noisy, incomplete, or uncertain. It provides an optimal estimate of the state of a system by combining the previous estimate with the new observation.
How to Implement Kalman Filter using OpenCV and Python?
Before we dive into the example code, we need to install the necessary libraries. We need to install NumPy and OpenCV in our Python environment. We can use the following command to install them:
