Computer Vision Roadmap

Week 1: Pixels and Foundations — Teaching Robots to See

Objective: This week, we’ll move beyond looking at images as just pictures and start seeing them as matrices of numbers. You'll learn the core math behind pixels, filters, and how to use OpenCV to perform digital "surgery" on images.

1. Introduction to Computer Vision

   • Focus on Lecture 1 and Lecture 2 to cover the basics.

2. OpenCV Documentation

   • OpenCV Python Documentation
   • Source for installation and core concepts.

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Week 2: Motion and Calibration

Objective: Learn about tracking objects, matching features, and fixing camera distortions.

1. Motion Detection and Optical Flow

   • Motion Detection Using OpenCV
   • Optical Flow in OpenCV

2. Feature Detection and Matching

   • Feature Detection in OpenCV

3. Camera Calibration and Perspective Transformation

   • Camera Calibration with OpenCV
   • Homography and Perspective Transformation

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Week 3: 3D Vision and Autonomy — Navigating the Real World

Objective: It’s time to give the robot a brain for the real world. We'll dive into 3D depth perception, real-time object detection with YOLO, and the "Holy Grail" of robotics: SLAM (Simultaneous Localization and Mapping).

1. Stereo Vision and Depth Estimation

   • Stereo Vision and Depth Maps

2. Object Detection Using YOLO

   • YOLO Object Detection (The Industry Standard)

3. Visual SLAM (vSLAM) and Localization

   • ORB-SLAM3: Open Source SLAM
   • Understanding vSLAM - MathWorks

4. ROS 2 and OpenCV Integration

   • ROS2 and OpenCV Integration Guide