Computer Vision - Object Tracking with OpenCV and Python from Coursera

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.

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Teaches practical skills in computer vision and object tracking using optical and dense optical flow, MeanShift, and CamShift

Taught in a hands-on manner within the browser using a pre-configured cloud desktop with Python, Jupyter, and Tensorflow pre-installed

Provides instant access to a cloud desktop with pre-installed software and data

Beginners in computer vision and object tracking will find this course accessible, as it builds a strong foundation for these topics

Requires fundamental knowledge of Python and OpenCV, which may not be suitable for absolute beginners

Access to the cloud desktop and video instructions is limited, which may interrupt the learning process

Reviews summary

Challenging computer vision project

This hands-on project, with 1-hour long video content, teaches you about computer vision object tracking using OpenCV and Python. Previous knowledge of Python and OpenCV is recommended for success in this project. The course is currently more accessible for those in North America, but improvements are being made to provide a better experience in other regions. This project provides access to cloud desktops with pre-installed software like Python, Jupyter, and TensorFlow. You'll learn about Optical and Dense Optical Flow, MeanShift, CamShift, Single Object Tracking, and Multi-Object Tracking. The project is well-received by learners, with many highlighting the streamlined approach with pre-configured cloud desktops.

1-hour long video content

"In this 1-hour long project-based course..."

Access to cloud desktops for hands-on practice

"On Rhyme, you do projects in a hands-on manner in your browser."

"For this project, you’ll get instant access to a cloud desktop with (e.g. Python, Jupyter, and Tensorflow) pre-installed."

Prior knowledge of Python and OpenCV is recommended

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

Some learners experienced technical issues

"My dudes, do not waist your time on this."

"The project has tons of error, it does not work correctly..."

"Also, it is very hard to understand what the instructor is saying, plus you are just coping the code he is writing."

Currently more accessible for learners in North America

"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."

Career center

Learners who complete Computer Vision - Object Tracking with OpenCV and Python will develop knowledge and skills that may be useful to these careers:

Computer Vision Engineer

Computer Vision Engineers design and develop systems that enable computers to interpret and understand visual data. This course provides a solid foundation in computer vision techniques, including object tracking, which is a key component in many computer vision applications. By learning about the different object tracking algorithms and how to implement them using OpenCV and Python, you will gain the skills necessary to build computer vision systems that can track objects in real-time.

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Robotics Engineer

Robotics Engineers design, build, and maintain robots, which often require computer vision capabilities to navigate and interact with the world around them. This course provides a foundation in computer vision techniques, including object tracking, which is essential for robots that need to track objects in real-time. By learning about the different object tracking algorithms and how to implement them using OpenCV and Python, you will gain the skills necessary to develop robots that can perform complex tasks in a variety of environments.

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Data Scientist

Data Scientists use data to solve problems and make predictions. Computer vision is a powerful tool for extracting insights from visual data, and object tracking is a key technique for analyzing video data. This course provides a foundation in computer vision techniques, including object tracking, which can be applied to a wide range of data science problems. By learning about the different object tracking algorithms and how to implement them using OpenCV and Python, you will gain the skills necessary to build data science models that can track objects in real-time.

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Machine Learning Engineer

Machine Learning Engineers design and develop machine learning models, which can be used to solve a wide range of problems, including object tracking. This course provides a foundation in computer vision techniques, including object tracking, which is a key component in many machine learning applications. By learning about the different object tracking algorithms and how to implement them using OpenCV and Python, you will gain the skills necessary to build machine learning models that can track objects in real-time.

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Software Engineer

Software Engineers design, develop, and maintain software systems. Computer vision is a rapidly growing field, and there is a high demand for software engineers with computer vision skills. This course provides a foundation in computer vision techniques, including object tracking, which is a key component in many computer vision applications. By learning about the different object tracking algorithms and how to implement them using OpenCV and Python, you will gain the skills necessary to build software systems that can track objects in real-time.

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Product Manager

Product Managers are responsible for the development and launch of new products. Computer vision is a powerful tool for creating new products, and object tracking is a key technique for developing products that can interact with the real world. This course provides a foundation in computer vision techniques, including object tracking, which can be applied to a wide range of products. By learning about the different object tracking algorithms and how to implement them using OpenCV and Python, you will gain the skills necessary to develop products that can track objects in real-time.

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User Experience Designer

User Experience Designers design and develop the user interface for products. Computer vision is a powerful tool for creating user interfaces that are intuitive and easy to use. This course provides a foundation in computer vision techniques, including object tracking, which can be used to develop user interfaces that can track objects in real-time. By learning about the different object tracking algorithms and how to implement them using OpenCV and Python, you will gain the skills necessary to design user interfaces that are both functional and visually appealing.

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Technical Writer

Technical Writers create documentation for software and other technical products. Computer vision is a complex field, and there is a high demand for technical writers who can explain computer vision concepts to a non-technical audience. This course provides a foundation in computer vision techniques, including object tracking, which can be used to create documentation for a wide range of computer vision products. By learning about the different object tracking algorithms and how to implement them using OpenCV and Python, you will gain the skills necessary to write documentation that is both accurate and easy to understand.

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Quality Assurance Analyst

Quality Assurance Analysts test software and other products to ensure that they meet quality standards. Computer vision is a powerful tool for automating quality assurance tasks, and object tracking is a key technique for testing products that interact with the real world. This course provides a foundation in computer vision techniques, including object tracking, which can be applied to a wide range of quality assurance tasks. By learning about the different object tracking algorithms and how to implement them using OpenCV and Python, you will gain the skills necessary to automate quality assurance tasks and improve the quality of software products.

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Technical Support Engineer

Technical Support Engineers provide technical support to customers who are using software and other products. Computer vision is a complex field, and there is a high demand for technical support engineers who can help customers troubleshoot computer vision problems. This course provides a foundation in computer vision techniques, including object tracking, which can be used to troubleshoot a wide range of computer vision products. By learning about the different object tracking algorithms and how to implement them using OpenCV and Python, you will gain the skills necessary to provide technical support to customers who are using computer vision products.

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Sales Engineer

Sales Engineers sell software and other products to customers. Computer vision is a rapidly growing field, and there is a high demand for sales engineers who can explain computer vision concepts to potential customers. This course provides a foundation in computer vision techniques, including object tracking, which can be used to sell a wide range of computer vision products. By learning about the different object tracking algorithms and how to implement them using OpenCV and Python, you will gain the skills necessary to sell computer vision products to potential customers.

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Marketer

Marketers develop and execute marketing campaigns to promote products and services. Computer vision is a powerful tool for creating marketing campaigns that are targeted and effective. This course provides a foundation in computer vision techniques, including object tracking, which can be used to create marketing campaigns that track customers' behavior and interests. By learning about the different object tracking algorithms and how to implement them using OpenCV and Python, you will gain the skills necessary to develop marketing campaigns that are both effective and engaging.

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Business Analyst

Business Analysts analyze business processes and make recommendations for improvements. Computer vision is a powerful tool for automating business processes and improving efficiency. This course provides a foundation in computer vision techniques, including object tracking, which can be used to automate a wide range of business processes. By learning about the different object tracking algorithms and how to implement them using OpenCV and Python, you will gain the skills necessary to analyze business processes and make recommendations for improvements that can be automated using computer vision.

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Project Manager

Project Managers plan, execute, and close projects. Computer vision is a complex field, and there is a high demand for project managers who can manage computer vision projects. This course provides a foundation in computer vision techniques, including object tracking, which can be used to manage a wide range of computer vision projects. By learning about the different object tracking algorithms and how to implement them using OpenCV and Python, you will gain the skills necessary to plan, execute, and close computer vision projects successfully.

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Data Analyst

Data Analysts collect, analyze, and interpret data to help businesses make decisions. Computer vision is a powerful tool for extracting insights from visual data, and object tracking is a key technique for analyzing video data. This course provides a foundation in computer vision techniques, including object tracking, which can be applied to a wide range of data analysis problems. By learning about the different object tracking algorithms and how to implement them using OpenCV and Python, you will gain the skills necessary to collect, analyze, and interpret visual data.

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Computer Vision - Object Tracking with OpenCV and Python

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Challenging computer vision project

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