Annotation BRUTE Forum Schedule Students: CZ EN
He who loves practice without theory is like the sailor who boards a ship without a rudder and compass and never knows where he may cast. — Leonardo Da Vinci (1452-1519)
And since geometry is the right foundation of all painting, I have decided to teach its rudiments and principles to all youngsters eager for art. — Albrecht Durer (1471-1528)
As for everything else, so for a mathematical theory: beauty can be perceived but not explained. — Arthur Cayley (1821–1895)
We will explain Euclidean, Affine, and Projective geometry basics, introduce a model of the perspective camera, and explain how images change when moving a camera. We will show how to compute camera poses and the 3D scene geometry from images. We will demonstrate the theory in practical panorama construction tasks, finding the camera pose, adding a virtual object to a real scene, and reconstructing a 3D model of a scene from its images. We will build on our previous knowledge of linear algebra and provide fundamentals of geometry for computer vision, computer graphics, augmented reality, image processing, and object recognition.
# | Date | Lecture T Pajdla. Elements of Geometry for Computer Vision and Computer Grahics |
---|---|---|
01 | 19.2. | TP: Geometry of CV & CG S V, LA [Sec. 2.1] S V, Image coordinate system [Sec. 5] V |
02 | 26.2. | TP: Mathematical model of the perspective camera [Sec. 6], Kronecker product [Sec. 2.5] S V1 V2 V3 |
03 | 04.3. | TP: Camera calibration and pose [Sec. 7.1] S V1 V2 |
04 | 11.3. | TP: Calibrated camera pose computation [Sec. 7.2, 7.3], Vector product [Sec. 2.2, 2.3] S V |
05 | 18.3. | VK: Homography [Sec. 8.1-8.5] S V1 V2 |
06 | 25.3. | TS: Image based camera localization S V1 V2 V3 |
— | 01.4. | Easter Monday |
07 | 08.4. | TS: Projective plane [Sec. 9.1-9.2] S V |
08 | 15.4. | TP: Vanishing points & line [Sec. 9.4, 9.5] projective space [Sec. 10] camera autocalibration [Sec. 11] S V |
09 | 22.4. | TP: Dual space [Sec. 2.4] lines under homography [Sec. 9.3] S0 S1 V |
10 | 29.4 | TP: Epipolar geometry [Sec. 12.1-12.2] Slides S0 S1 V |
11 | 06.5 | TP: 3D reconstruction with a calibrated camera [Sec. 12.3, 12.4] S0, S1, V |
12 | 13.5. | TP: Calibrated camera motion computation [Sec. 12.5] S0, S1, V |
13 | 20.5. | TS: 3D Reconstruction pipelines SV |
Martin Matoušek, Viktor Korotynskiy , Vojtěch Pánek
See Labs for more details.
The exam consists of a written and an oral part. It is required to achieve at least 50% of points from the written exam to be admitted to the oral exam. The grade depends on the exam (40%), tests (30%), and homework (30%). You may skip the oral exam if you are satisfied with the result after the written exam.
Exam content:
Written exam terms
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Oral exam organization: