Computer Vision - Object Tracking with OpenCV and Python

In this 1-hour long project-based course, you will learn how to do Computer Vision Object Tracking from Videos. At the end of the project, you'll have learned how Optical and Dense Optical Flow work, how to use MeanShift and CamShist and how to do a Single and a Multi-Object Tracking.

This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your Internet browser so you can just focus on learning. For this project, you’ll get instant access to a cloud desktop with (e.g. Python, Jupyter, and Tensorflow) pre-installed.

Prerequisites:
In order to be successful in this project, you should have a fundamental knowledge of Python and OpenCV.

Notes:
- You will be able to access the cloud desktop 5 times. However, you will be able to access instructions videos as many times as you want.
- This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.