Video Stabilization Using Point Feature Matching in OpenCV

6,000.00

Video Stabilization Using Point Feature Matching in OpenCV

100 in stock

SKU: Video Stabilization Using Point Feature Matching in OpenCV Category:

Description

Video Stabilization Using Point Feature Matching in OpenCV

In this project,we explain an implement a simple Video Stabilizer using a technique called Point Feature Matching in OpenCV library. We will discuss the algorithm and share the code(in python) to design a simple stabilizer using this method in OpenCV. In this project is to reduce blurring associated with the motion of a camera during exposure. Such as image distortion, image blurring etc.This technique shifts the electronic image from frame to frame of video, enough to counteract the motion. It uses pixels outside the border of the visible frame to provide a buffer for the motion.

We using an algorithm called Lucas-Kanade Optical Flow named after the inventors of the algorithm.This method involves tracking a few feature points between two consecutive frames. The tracked features allow us to estimate the motion between frames and compensate for it.For video stabilization, we need to capture two frames of a video, estimate motion between the frames, and finally correct the motion.

Additional information

Weight1.000000 kg

Reviews

There are no reviews yet.

Be the first to review “Video Stabilization Using Point Feature Matching in OpenCV”

Your email address will not be published. Required fields are marked *

four × 1 =

This site uses Akismet to reduce spam. Learn how your comment data is processed.