3D Computer Vision

Computer Vision

Lectures: on Mondays, 8:25-9:55 , lecture hall 0.79  0.79 Jánossy Lajos lecture hall,  (North Building)

Practices:

  • On Fridays 17.45-19.15, South building at
    • South building 0-220 Kárteszi Ferenc room
    • South building 0-311 Konig terem room
    • South building 0-312 Gallai Tibor room

Teachers:

Demonstrators

  • Máté Poór
  • Muhammad Rafi Faisal

Agenda

WeekLectureLaboratory
1st – Registration week
2ndIntroductionVehicle and sensor kit demonstration
( videos of 2023)
3rdEstimation theory: inhomogeneous linear systemsOpenCV installation, GUI by OpenCV
4thLagrange multipliers; homogeneous linear systems, point-line/plane distancesAffine Transformations
5thRandom Sampling Consensus (RANSAC) RANSAC (Whiteboard)
6thOptimal Plane Fitting; SVD; Camera modelsPointset visualization

Topics for oral exams

  1. Basic estimation theory: solution for homogeneous and inhomogeneous linear system of equations.
  2. Robust fitting methods: RANSAC, LO-RANSAC.
  3. Multi-model fitting: sequential RANSAC, MultiRANSAC
  4. Camera models: perspective camera, orthogonal projection, weak-perspective camera.
  5. Calibration of perspective camera using a spatial calibration object: Estimation and decomposition of projection matrix.
  6. Chessboard-based calibration of perspective cameras. Radial and tangential distortion.
  7. Plane-plane homography. Panoramic images by homographies.
  8. Estimation of homography. Data normalization.
  9. Basics of epipolar geometry. Essential and fundamental matrices. Rectification.
  10. Estimation of essential and fundamental matrices. Data normalization. Decomposition of essential matrix.
  11. Triangulation for both standard and general stereo vision.
  12. Stereo vision for planar motion.
  13. Tomasi-Kanade factorization: multi-view reconstruction by orthogonal and weak-perspective camera models.
  14. Reconstruction by merging stereo reconstructions. Registration of two point sets by a similarity transformation.
  15. Numerical multi-view reconstruction: bundle adjustment.
  16. Tomasi-Kanade factorization with missing data.
  17. Reconstruction by special devices: laser scanning, depth camera, LiDAR