Lecture Introduction

All projects and assignments are based on '2024 Spring Computer Vision(1)' by KNU CVMIP Lab.

This lecture is 'Blended Learning'; Video Lecture for theories, In-person Class for coding practice.

Midterm Exam Information

Week.02 ~ Week.07 : Closed-book Hand-writing (From Lecture and Assignments)

1. Homogeneous Coordinate Calculation
2. Sobel Mask Direction Vector Calcualtion
3. Moravec Algorithm Confidence Calculation
4. Covariance Matrix of Test Scores from Two Students
5. Hand-writing Code: Dissolve of Two Images (week03)

Final Exam Information

Week.09 ~ Week.12 : Closed-book Hand-writing (Includes Basis from Previous Lecture)

1. Euclidean Distance Calculation of Two Vectors
2. SIFT : Feature Descriptor Direction Vector Quantization, Weighted Vector, and Normalized Histogram
3. PCA : Calculate Eigen Value and Vector of Two Images and Dimensionality Reduction
4. Hand-writing Code: Harris Corner Confidence Map Calculation (p = Gdy2, q = Gdx2, r = Gdxy)