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image for course Computer Vision Onramp

Computer Vision Onramp

Learn the basics of computer vision by applying a typical workflow—tracking-by-detection—to video of turtles crawling towards the sea. You will learn about the role of features in computer vision, how to label data, train an object detector, and track wildlife in video.

Course modules

Introduction

Familiarize yourself with computer vision concepts covered and the course.

Lessons:
  • Course Overview

Video Data in MATLAB

Import video data, inspect properties, and process frames.

Lessons:
  • Create a Video Reader
  • Read Video Data

Image Features in Computer Vision

Detect, extract, and match features in two images.

Lessons:
  • Detect and Extract Features from a Reference Image
  • Match Features in an Image with a Reference

Object Detection

Create ground truth data, and train and use an object detector.

Lessons:
  • Prepare Ground Truth Data
  • Detect and Count Objects
  • Detect Objects in Each Video Frame

Object Tracking

Track a single object through an occlusion using an object detector and Kalman filter.

Lessons:
  • Set Up a Kalman Filter for Tracking
  • Track a Single Object

Conclusion

Learn next steps, and give feedback on the course.

Lessons:
  • Additional Resources
  • Survey

Format:Self-paced

Language:English

Language

  • Hands-on exercises with automated feedback
  • Access to MATLAB through your web browser
  • Shareable progress report and course certificate

Image Processing Onramp

Learn the basics of practical image processing techniques in MATLAB.

Image Processing with MATLAB

Learn practical image processing workflows in MATLAB.

Deep Learning Onramp

Get started quickly using deep learning methods to perform image recognition.

MATLAB Coder Onramp

Learn the basics of C code generation from MATLAB functions.

Object Detection with Deep Learning

Use deep learning for multiclass object detection with YOLO, pretrained networks, and evaluation techniques.

Image Processing Onramp

Learn the basics of practical image processing techniques in MATLAB.

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