OpenCV Basics for Robotics Course - Python
Learn how to work with OpenCV in ROS.
Relate to the environment, recognize patterns, understand concepts of pixels, colors, borders, detection of objects, detection of people, faces, etc. They make this combination one of extraordinary potential when it comes to obtaining useful information for a robot about the system that surrounds it. A clear example is the use of cameras in robotics, from drones to mobile robots. The use of cameras has been a constant for quite some time, and it is a tool that cannot be underestimated.
What you will learn
- Unit 2: Computer Vision Basics
- Unit 3: People related OpenCV functions
- Unit 4: Feature Matching
- Unit 5: ARTags (Augmented Reality)
- Unit 6: Course Project
Introduction to the Course
Unit for previewing the contents of the Course.
Computer Vision Basics
cv_bridge, color spaces and color filtering, edge detection, and a brief introduction to convolutionsmorphological transformations.
People-related OpenCV functions
Face Detection (Haar cascades) and People Detection and Tracking (HOG).
Features from Accelerated Segment Test (FAST), Binary Robust Independent Elementary Features (BRIEF)and Oriented FAST and Rotated BRIEF (ORB).
ARTags (Augmented Reality)
Learn how to use ARtags (Augmented Reality) in robotics.
There is a dangerous person in this city, and many possible suspects are close to your robot. You must detect all the people and highlight the dangerous person.
Christian Alberto Chávez Vásquez
Master Degree in Robotics, Automation and Home Automation and currently studying another Master Degree in Smart Cities and Smart Grids. He has worked in ROS projects with navigation, exploration, industrial robotics and artificial vision.
Degree in Mechatronics Engineering, currently studying a Master Degree in Data science. Is passionate about programing with a huge interest on machine learning and computer vision related algorithms.