MATLAB & Simulink


Computer Vision with MATLAB

Course Highlights

This one-day course provides hands-on experience with performing computer vision tasks. Examples and exercises demonstrate the use of appropriate MATLAB® and Computer Vision System Toolbox™ functionality. 

Topics include:

  • ​Importing, displaying, and annotating videos

  • Detecting objects in videos

  • Estimating motion of objects

  • Tracking a single object or multiple objects

  • Removing lens distortion and measuring planar objects 

Who Should Attend

Engineers, researchers, scientist who are involved in development of computer vision applications. 

Course Prerequisites

MATLAB Fundamentals, Image Processing with MATLAB 

Course Benefits

Upon completion of the course, the participants will be able to use Computer Vision System Toolbox to

- detect specific objects

- estimate motion of objects

- track a single object or multiple objects - remove distortion and measure planar object size 



Upcoming Program

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Mathworks Sole and Authorised Distributor and Training Partner

Course Outline

Importing, Visualizing and Annotating Videos

Objective: Import videos into MATLAB, as well as annotate and visualize them. The focus is on using System Objects for performing iterative computations on video frames.

-Importing and displaying video files

-Highlighting objects by drawing markers and shapes like rectangles

-Combining and overlaying two images

-Performing iterative computations on video frames 


Detecting Objects 
Objective: Utilize machine learning and deep learning algorithms for complex object detection.

- Marking objects of interest in training images

- Training and using a cascade object detector

- Using a deep learning object detector 


Estimating Motion 

Objective: Estimate direction and strength of motion in a video sequence. 

- Understanding motion perception in images

- Estimating motion using optical flow methods

Tracking Objects

Objective: Track single and multiple objects and estimate their trajectory. Handle occlusion by predicting object position.

- Tracking single objects using a Kalman Filter

- Tracking multiple objects using a GNN tracker 

Camera Calibration  

Objective: Remove lens distortion from images. Measure size of planar objects. Estimating intrinsic, extrinsic, and lens distortion parameters of a camera

- Visualizing the calibration error

- Removing lens distortion

- Measuring planar objects in real-world units