Warning

Schedule: B4M33TDV BE4M33TDVXP33VID
Students: B4M33TDV BE4M33TDVXP33VID

# TDV − 3D Computer Vision (Winter 2017)

## Motivation

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.

 Fig. 1: an example of input images Fig. 2: resulting vrml model

## Lectures: Tuesday 12:45-14:15, KN:E-126

Lecture slides are ready for download before the lecture. They get annotated during the lecture and appear here after the lecture.

Week Date Updated Slides Annotated Slides Lecture Content
1 3.10. Introduction (large!) Course Overview 3D computer vision, its goals and applications, course overview
Lecture 1 L1 annotated basic geometry of points and lines
2 10.10. Lecture 2 L2 annotated homography, perspective camera
3 17.10. Lecture 3 L3 annotated projection matrix decomposition, optical center, ray, axis, plane; vanishing point, cross-ratio
4 24.10. Lecture 4 L4 annotated camera calibration from vanishing points, camera resection from 6 points
5 31.10. Lecture 5 L5 annotated critical configurations for resection, the exterior orientation problem, epipolar geometry, epipolar constraint
6 7.11. Lecture 6 L6 annotated essential matrix decomposition, 7-point algorithm for fundamental matrix estimation, 5-point algorithm for essential matrix estimation, triangulation by algebraic error minimization
7 14.11. Lecture 7 L7 annotated reprojection error, Sampson error correction, the golden standard triangulation method
8 21.11. Lecture 8 L8 annotated local optimization, robust error function
9 28.11. Lecture 9 L9 annotated optimization by random sampling, MH sampler, RANSAC
10 5.12. Lecture 10 L10 annotated camera system reconstruction, bundle adjustment
11 12.12. Lecture 11 L11 annotated gauge freedom in bundle adjustment, introduction to stereovision
12 19.12. Lecture 12 L12 annotated epipolar rectification, occlusion constraint
13 2.1. Lecture 13 L13 annotated matching table, Marroquin's WTA matching algorithm, maximum-likelihood matching algorithm, ordering constraint, stereo matching algorithm comparison
14 9.1. no lecture

## Exercises (requirements)

Teacher: Martin Matoušek

Details about exercises (technical content and assessment) are in the separate section Exercises.

Notice: according to the study and examination code of CTU1), attendance at lectures is not mandatory (but recommended). However, students attending exercises are required to be theoretically prepared. The necessary theory is explained at the preceding lectures and can be also found in the recommended literature.

#### Requirements for the Credit

1. Attending the exercises is mandatory, two absences are allowed.
2. Submission/presentation of all required intermediate results.
3. Submission of all required elementary methods that must pass automatic check.
4. Submission of results of the term project.
5. Submission of all homework problems assigned during lectures.

## Assessment

Student assessment is based on scoring in the nominal range 0−100 points. There is also possibility to obtain some additional bonus points. The points are allocated to lectures, labs, homework problems and exam as follows:

Nominal points Minimal points Bonus points
Exercises 45
Homework assignments given at lectures 9 14
Exam – Test 1 10 3
Exam – Test 2 24 6
Exam – oral 12
Total 100 +14

Assessment of Exercises is described in detail in the section of exercises.

The total of all points, including the bonuses is arithmetically rounded up and clipped at 100.

The grade is then given by the standard table (100−90⇒A, 89−80⇒B, 79−70⇒C, 69−60⇒D, 59−50⇒E, ≤ 49 ⇒ F).

## Exam

The 1st exam test is done during the semester. The 2nd test is part of the exam at the end. The exam has two parts, usually, one day we do the test and the other day we have the oral part. The oral part is mandatory to achieve the A–B grades; it tests the ability to solve small problems; at least 5 points must be achieved, otherwise the final grade is C.

 Lectures: Radim Šára Exercises: Martin Matoušek sara@cmp.felk.cvut.cz Martin.Matousek@cvut.cz KN, room 103 Dejvice, CIIRC, room B606 phone (22435) 7203 phone (22435) 4221