MATLAB and Simulink Training

Computer Vision with MATLAB

Course Details

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

Day 1 of 1

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

Level: Intermediate


Duration: 1 day

Languages: English, 日本語, 한국어, 中文