3D Computer Vision
Code | Completion | Credits | Range | Language |
---|---|---|---|---|
A4M33TDV | Z,ZK | 6 | 2P+2C | Czech |
- Relations:
- It is not possible to register for the course A4M33TDV if the student is concurrently registered for or has already completed the course AE4M33TDV (mutually exclusive courses).
- The requirement for course A4M33TDV can be fulfilled by substitution with the course AE4M33TDV.
- It is not possible to register for the course A4M33TDV if the student is concurrently registered for or has previously completed the course AE4M33TDV (mutually exclusive courses).
- It is not possible to register for the course A4M33TDV if the student is concurrently registered for or has previously completed the course BE4M33TDV (mutually exclusive courses).
- Course guarantor:
- Lecturer:
- Tutor:
- Supervisor:
- Department of Cybernetics
- Synopsis:
-
This course introduces methods and algorithms for 3D geometric scene reconstruction from images. The student will understand these methods and their essence well enough to be able to build variants of simple systems for reconstruction of 3D objects from a set of images or video, for inserting virtual objects to video-signal source, or for computing ego-motion trajectory from a sequence of images. The labs will be hands-on, the student will be gradually building a small functional 3D scene reconstruction system.
- Requirements:
-
Knowledge equivalent to Geometry for Computer Vision and Graphics and Computer Vision Methods.
Detailed up-to-date information on the course at http://cw.felk.cvut.cz/doku.php/courses/a4m33tdv/start
- Syllabus of lectures:
-
1. 3D computer vision, goals and applications, the course overview
2. Real perspective camera
3. Calibration of real perspective camera
4. Epipolar geometry
5. Computing camera matrices and 3D points from sparse correspondences
6. Autocalibration
7. Consistent multi-camera reconstruction
8. Optimal scene reconstruction
9. Epipolar image rectification
10. Stereoscopic vision
11. Algorithms for binocular stereoscopic matching, multi-camera
algorithms
12. Shape from shading and contour
13. Shape from texture, defocus, and color
14. Surface reconstruction
- Syllabus of tutorials:
-
1. Labs introduction and overview, experimental data, entrance test
2. Camera calibration without radial distortion from a known scene
3. Camera calibration with radial distortion from a known scene
4. Computing epipolar geometry from 8 points
5. Computing epipolar geometry from 7 points, RANSAC
6. Constructing projection matrices from epipolar geometry, computing camera motion and scene structure
7. Autocalibration of intrinsic camera parameters
8. Consistent reconstruction of a many-camera system
9. Accuracy improvement by bundle adjustment
10. Time slot to finish all pending assignments
11. Epipolar rectification for stereoscopic vision
12. Stereoscopic matching by dynamic programming
13. 3D point cloud reconstruction
14. 3D sketch reconstruction
- Study Objective:
-
To master conceptual and practical knowledge of the basic methods in 3D computer vision.
- Study materials:
-
R. Hartley and A. Zisserman. Multiple View Geometry. 2nd ed. Cambridge
University Press 2003.
Y. Ma, S. Soatto, J. Kosecka, S.S. Sastry. An Invitation to 3D
Vision. Springer 2004.
- Note:
- Further information:
- http://cw.felk.cvut.cz/doku.php/courses/a4m33tdv/start
- No time-table has been prepared for this course
- The course is a part of the following study plans: