Macroblock Matching Motion Visualization

This repository contains a Python script that processes video files to detect and visualize motion vectors using block-matching algorithms. The script analyzes each frame of a video, compares blocks between consecutive frames, and draws arrows to represent motion. The processed frames are then compiled into a new video.

Features

• Extracts frames from a video.
• Compares blocks of pixels between consecutive frames.
• Draws arrows to indicate motion between blocks.
• Saves processed frames and compiles them into a new video.

Dependencies

The script requires the following Python packages:

• numpy
• opencv-python

You can install the required packages using pip:

pip install numpy opencv-python

Usages

File Setup

• Place your video file in the SourceVideo folder.
• Ensure the VideoFrames and OutputFrames directories exist or create them.

Script Setup

• Change the variables video_name and output_video_name to match the input video name [WITH EXTENSION] and desired output name

Parameters

• block_radius = 2
• pixel_search_radius = 35
• Tmin = 400
• Tmax = 1000

The above parameters can be tweaked to provide more optimal results based on your input video resolution and noise levels.

Demonstration