Object Tracking and Motion Detection with Computer Vision (Coursera)

Offered by MathWorks,
Object Tracking and Motion Detection with Computer Vision (Coursera)

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.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

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.

Course 3 of 3 in the Computer Vision for Engineering and Science Specialization.

Syllabus

WEEK 1: Detecting Objects
WEEK 2: Motion Detection
WEEK 3: Detection and Tracking
WEEK 4: Final Project

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Data Science Project: MATLAB for the Real World (Coursera) Coursera
MathWorks

Data Science Project: MATLAB for the Real World (Coursera)

Like most subjects, practice makes perfect in Data Science. In the capstone project, you will apply the skills learned across courses in the Practical Data Science with MATLAB specialization to explore, process, analyze, and model data. You will choose your own pathway to answer key questions with the provided data. To complete the project, you must have mastery of the skills covered in other courses in the specialization. The project will test your ability to import and explore your data, prepare the data for analysis, train a predictive model, evaluate and improve your model, and communicate your results.

Jul 13th 2026
4 Weeks
Introdução ao Controle Moderno (Coursera) Coursera
Instituto Tecnológico de Aeronáutica

Introdução ao Controle Moderno (Coursera)

Este curso lhe dará a base necessária para entender técnicas mais avançadas de controle moderno. Você aprenderá como representar a dinâmica de um sistema no espaço de estados, como analisar um sistema no espaço de estados, como projetar uma realimentação de estado e como projetar um observador de estado.

Jul 27th 2026
5-12 Weeks
Exploratory Data Analysis with MATLAB (Coursera) Coursera
MathWorks

Exploratory Data Analysis with MATLAB (Coursera)

In this course, you will learn to think like a data scientist and ask questions of your data. You will use interactive features in MATLAB to extract subsets of data and to compute statistics on groups of related data. You will learn to use MATLAB to automatically generate code so you can learn syntax as you explore. You will also use interactive documents, called live scripts, to capture the steps of your analysis, communicate the results, and provide interactive controls allowing others to experiment by selecting groups of data.

Jul 13th 2026
5-12 Weeks
Data Science Companion (Coursera) Coursera
MathWorks

Data Science Companion (Coursera)

The Data Science Companion provides an introduction to data science. You will gain a quick background in data science and core machine learning concepts, such as regression and classification. You’ll be introduced to the practical knowledge of data processing and visualization using low-code solutions, as well as an overview of the ways to integrate multiple tools effectively to solve data science problems.

Jul 17th 2026
4 Weeks
Visual Perception for Self-Driving Cars (Coursera) Coursera
University of Toronto

Visual Perception for Self-Driving Cars (Coursera)

Welcome to Visual Perception for Self-Driving Cars, the third course in University of Toronto’s Self-Driving Cars Specialization. This course will introduce you to the main perception tasks in autonomous driving, static and dynamic object detection, and will survey common computer vision methods for robotic perception. By the end of this course, you will be able to work with the pinhole camera model, perform intrinsic and extrinsic camera calibration, detect, describe and match image features and design your own convolutional neural networks.

Jul 13th 2026
5-12 Weeks
Machine Learning (Coursera) Coursera
Stanford University

Machine Learning (Coursera)

Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Many researchers also think it is the best way to make progress towards human-level AI. In this class, you will learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself. More importantly, you'll learn about not only the theoretical underpinnings of learning, but also gain the practical know-how needed to quickly and powerfully apply these techniques to new problems.

Jul 13th 2026
5-12 Weeks
Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning (Coursera) Coursera
DeepLearning.AI

Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning (Coursera)

If you are a software developer who wants to build scalable AI-powered algorithms, you need to understand how to use the tools to build them. This course is part of the upcoming Machine Learning in Tensorflow Specialization and will teach you best practices for using TensorFlow, a popular open-source framework for machine learning.

Jul 20th 2026
4 Weeks
Computer Vision Basics (Coursera) Coursera
University at Buffalo,The State University of New York

Computer Vision Basics (Coursera)

By the end of this course, learners will understand what computer vision is, as well as its mission of making computers see and interpret the world as humans do, by learning core concepts of the field and receiving an introduction to human vision capabilities. They are equipped to identify some key application areas of computer vision and understand the digital imaging process. The course covers crucial elements that enable computer vision: digital signal processing, neuroscience and artificial intelligence.

Jul 13th 2026
4 Weeks