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Object Tracking and Motion Detection with Computer Vision

In the third and final course of the Computer Vision for Engineering and Science specialization, you will learn to track objects and detect motion in videos. Tracking objects and detecting motion are difficult tasks but are required for applications as varied as microbiology and autonomous systems. To track objects, you first need to detect them. You’ll use pre-trained deep neural networks to perform object detection. You’ll also use optical flow to detect motion and use the results to detect moving objects. At the end of this course, you’ll apply all the skills learned in this specialization to a final project. You’ll take the role of an engineer being asked to track cars on a busy highway with the added challenge of counting each vehicle and its direction. You will use MATLAB throughout this course. MATLAB is the go-to choice for millions of people working in engineering and science and provides the capabilities you need to accomplish your computer vision tasks. You will be provided free access to MATLAB for the course duration to complete your work. To be successful in this specialization, it will help to have some prior image processing experience. If you are new to image data, it’s recommended to first complete the Image Processing for Engineering and Science specialization.

Status: Traffic Flow Optimization
Status: Convolutional Neural Networks
BeginnerCourse13 hours

Featured reviews

SM

5.0Reviewed Mar 12, 2024

Perfect course to get hands-on experience of applications of computer vision techniques to solve a problem.

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Christopher Adewole
2.0
Reviewed Aug 17, 2024
arnulfo perez
5.0
Reviewed Dec 2, 2024
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Reviewed Mar 13, 2024
Nick Sander
5.0
Reviewed Apr 25, 2025
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5.0
Reviewed Dec 30, 2022
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Reviewed Feb 13, 2026
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5.0
Reviewed Sep 9, 2024
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SAIKAT SINHAMAHAPATRA
5.0
Reviewed Oct 29, 2023
ANANT PREET SINGH REEN
5.0
Reviewed Nov 22, 2023
PALASA DHANUSHKA
4.0
Reviewed Apr 7, 2026
Surya Balan S
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Reviewed Aug 2, 2024
Charlie Macdonald
1.0
Reviewed Sep 17, 2024