Advanced concepts in video data analysis

The following concepts are fundamental in video data analysis and are commonly applied in real-world machine learning applications. Let’s see those concepts briefly here. Please note that the implementation of some of these concepts is beyond the scope of this book.

Motion analysis in videos

Concept: Motion analysis involves extracting and understanding information about the movement of objects in a video. This can include detecting and tracking moving objects, estimating their trajectories, and analyzing motion patterns.

Tools: OpenCV (for computer vision tasks) and optical flow algorithms (e.g., the Lucas-Kanade method).

Let’s see the overview of the code for motion analysis in video data.

Initialization: Open a video file and set up parameters for Lucas-Kanade optical flow:

import cv2
import numpy as np
# Read a video file
cap = cv2.VideoCapture('/<your_path>/CricketBowling.mp4')
# Initialize...