• Lecture 1: Overview
• Lecture 2: Pixel-based processing
• Lecture 3: Filtering and edge detection
• Lecture 4:  Segmentation
• Lecture 5:  Stereo vision
• Lecture 6:  Motion
• Lecture 7:  Color
• Lecture 8:  Image formation
• Lecture 9:  Projective geometry
• Lecture 10:  Strong vs. weak AI
• Lecture 11:  Vision in nature
• Lecture 12:  Classification
• Lecture 13:  Shape
• Lecture:  SURF
• Lecture 14:  Texture
• Lecture 15:  Model fitting
• Lecture 16:  Camera calibration
• Lecture 17:  Multi-view geometry
• Lecture 18:  Structure from motion

Classic papers in computer vision

Book draft:

• Chapter 1:  Introduction
• Chapter 2:  Pixel-based processing
• Chapter 3:  Filtering
• Chapter 4:  Binary image processing
• Chapter 7:  Segmentation
• Chapter 13:  Stereo
• Appendix:  Programming