Computer Vision
Lectures: on Mondays, 8:25-9:55 , lecture hall 0.79 0.79 Jánossy Lajos lecture hall, (North Building)
Practices:
- On Wednesdays 17.55-19.25, South building at
- South building 0-311 Konig terem room
- South building 0-312 Gallai Tibor room
- (South building 0-220 Kárteszi Ferenc room)
Teachers:
- Levente Hajder
- Tamás Tófalvi
- Tarlan Ahadli
Demonstrators
- Máté Poór
- Muhammad Rafi Faisal
Agenda
| Week | Lecture | Laboratory |
| 1st – Registration week | ||
| 2nd | Introduction | Vehicle and sensor kit demonstration ( videos of 2023) |
| 3rd | Estimation theory: inhomogeneous linear systems | OpenCV installation, GUI by OpenCV |
| 4th | Lagrange multipliers; homogeneous linear systems, point-line/plane distances | Affine Transformations |
| 5th | Random Sampling Consensus (RANSAC) | RANSAC (Whiteboard) |
| 6th | Optimal Plane Fitting; SVD; Camera models | Pointset visualization (Whiteboard) |
| 7th | Back-projection. Introduction to homographies. | |
| 8th | National holiday (break) | |
Topics for oral exams
- Basic estimation theory: solution for homogeneous and inhomogeneous linear system of equations.
- Robust fitting methods: RANSAC, LO-RANSAC.
- Multi-model fitting: sequential RANSAC, MultiRANSAC
- Camera models: perspective camera, orthogonal projection, weak-perspective camera.
- Calibration of perspective camera using a spatial calibration object: Estimation and decomposition of projection matrix.
- Chessboard-based calibration of perspective cameras. Radial and tangential distortion.
- Plane-plane homography. Panoramic images by homographies.
- Estimation of homography. Data normalization.
- Basics of epipolar geometry. Essential and fundamental matrices. Rectification.
- Estimation of essential and fundamental matrices. Data normalization. Decomposition of essential matrix.
- Triangulation for both standard and general stereo vision.
- Stereo vision for planar motion.
- Tomasi-Kanade factorization: multi-view reconstruction by orthogonal and weak-perspective camera models.
- Reconstruction by merging stereo reconstructions. Registration of two point sets by a similarity transformation.
- Numerical multi-view reconstruction: bundle adjustment.
- Tomasi-Kanade factorization with missing data.
- Reconstruction by special devices: laser scanning, depth camera, LiDAR