Computer Vision Fundamentals
Coming Soon
This lesson is currently under development. Check back soon for comprehensive content covering:
- Image Processing Basics: Filtering, edge detection, feature extraction (SIFT, ORB)
- Object Detection: YOLO, Faster R-CNN, SSD, real-time detection for robotics
- Semantic Segmentation: FCN, U-Net, Mask R-CNN for scene understanding
- Depth Estimation: Stereo vision, monocular depth, structured light sensors
- Perception Pipelines: End-to-end vision systems for robot navigation and manipulation
Expected Completion: This lesson will be available soon.
Learning Objectives
By the end of this lesson, you will be able to:
- Implement object detection for robot perception tasks
- Understand semantic segmentation for scene understanding
- Estimate depth from camera images using multiple approaches
- Design perception pipelines for robotics applications
Further Reading
- Computer Vision: Algorithms and Applications by Richard Szeliski
- YOLO: Real-Time Object Detection — Fast detection for robots
- OpenCV Documentation — Computer vision library
What's Next?
Continue to Lesson 4: Natural Language Processing Basics to learn how robots understand human language.
This lesson is part of Chapter 2: AI Fundamentals Review