Book Image

Learn Computer Vision with Python and OpenCV [Video]

By : Kathiravan Natarajan
Book Image

Learn Computer Vision with Python and OpenCV [Video]

By: Kathiravan Natarajan

Overview of this book

<p>Computer vision solves imaging problems that cannot be solved using ordinary systems and sensors. OpenCV is one of the most popular Computer Vision libraries and helps you write faster code.</p> <p>This course begins with the basics of loading and working with images. You will detect colored objects in your images easily. You will also use tools to build and apply filters in your photos and track objects in a video.</p> <p>By the end of the course, you will have a firm grasp of Computer Vision techniques using OpenCV libraries. This course will be your gateway to the world of data science.</p> <p>The code bundle is placed at:&nbsp;<a href="https://github.com/PacktPublishing/Learn-Computer-Vision-with-Python-and-OpenCV-Video" target="_blank">https://github.com/PacktPublishing/Learn-Computer-Vision-with-Python-and-OpenCV-Video</a></p> <h1>Style and Approach</h1> <p>This course will teach you the skills required to develop computer vision applications using Python with practical examples.</p>
Table of Contents (4 chapters)
Chapter 4
Video Analysis
Content Locked
Section 4
Optical Flow Using Lucas-Kanade and Dense Optical Flow
Are those optical flow assumptions help me in finding the optical flow of the object in the video? - Recollect the optical flow assumptions - Explain how to implement Lucas Kanade optical flow - Explain how to implement dense optical flow