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# TDV − exercises

The goal of exercises is to practice the 3D reconstruction techniques explained at lectures. During the exercises, students will build up complete system for reconstruction of a surface of a 3D scene given its images. Implementation if this system and its use for the reconstruction is solved as a term project, and it is subject of the exercises. Students are working individually during the exercises as well as on the term project.

Whole system is build from several building blocks − elementary methods. These methods will be explained in the lectures gradually. Students will implement some methods, another methods are already available and the task is to integrate them into the system.

Whole problem is separated into following four phases. These consist of methods that are related and possibly cooperates. Each phase represents relatively independent part, and it covers several week classes. There are defined required results for each phase. Whole project is finished by submission of a final results of reconstruction.

#### Phases

1. Input data capture and preprocessing
2. Epipolar geometry on image pairs.
3. Multiple cameras and structure of the scene.
4. Surface reconstruction.

## Implementation

The term project and other tasks should be solved using the Matlab environment. There are some methods, that students need not implement 1). These methods can be obtained from the code repository. These codes can be subject of small evolution and bug-fixing. It is thus recommended always to use the latest revision. In case that you found a bug, please announce this using the forum.

During the implementation, students should build a set (library, toolbox) of general elementary tools and methods. The functions of this Toolbox of Elementary and Helper Functions will be specified during the term. This toolbox should be submitted (repeatedly, as the number of functions will grow) to the upload system for the automatic check of validity (_toolbox assignment).

Important: Without prior permission from the teacher, it is not allowed to use different software tools than the ones specified in the description. However, this does not apply for visualization and presentation of results (vrml and so).

## Schedule of Exercises

Week Date Phase Details Submission Points
1. 3.10. 1. Input dataIntroduction, term project specification, capture, camera calibration.
0. Basic geometry, MatlabPoints and lines in a plane.
2. 10.10. Perspective camera. Task 0-1 1
3. 17.10. Robust maximum likelihood estimation of a planar line. Task 0-2 2
4. 24.10. 2. Seeking of Sparse CorrespondencesWBS matcher, sparse correspondences. Task 0-3 3
5. 31.10. 0. Basic geometry (continued) Estimation of two homographies Task 2 3
6. 7.11. 3. Robust estimation of calibrated epipolar geometry of image pairs Task 0-4 4
7. 14.11. –continued
8. 21.11. 4. Multiple cameras and structure of the scene Calibration of poses of a set of cameras
9. 28.11. Sparse point cloud reconstruction Task3 10
10. 5.12. Test 1
11. 12.12. Optimisation of points and cameras by bundle adjustment
12. 19.12. 5. Surface reconstruction Epipolar rectification and dense matching. Dense point cloud reconstruction. Task 4 14
13. 2.1. Final 3D surface reconstruction
14. 9.1. Consultation, reserve, credit (if eligible) Task 5 8

## Assessment of Exercises

#### Continuous work

There is 45 pts assigned for a continuous work during exercises.

Small problems and the term project are solved during the labs. Successfully solved and demonstrated (to the teacher) or submitted (to the upload system where required) problem is credited by appropriate number of points. All problems and project sub-tasks have deadlines. Later demonstration/submission will be penalized by -15% of the nominal points for the task if one week later or by -30% if two and more weeks later.

1. three vrml models (in archive, assignment vrml),
2. your codes (in archive, assignment codes).