| ProjectForm | |
|---|---|
| Title: | Optimization Algorithms for 3D Computer Vision: |
| Abstract: | Not only in Computer Vision but also in many other applications, optimization algorithms are crucial methods for error minimization in order to get good computational results. In Computer Vision these algorithms are used for estimating e.g. homographies, projection matrices, fundamental matrices, or tensors optimally. Especially non-linear optimization methods like Levenberg-Marquardt, Gradient Descent or Gauss-Newton iteration (which might be known from Konkrete Mathematik) are essential for optimal estimation. This SEP covers the implementation of these algorithms first in Matlab, a powerful and easy-to-learn tool for mathemtical computations, and in C++. Moreover, an application for testing the optimization algorithms shall be implemented, which can be chosen from the Computer Vision area, e.g. mosaicing, or 3D scene reconstruction from 2 or multiple views. Prerequisite is an advanced knowledge in C++ programming. |
| Student: | Moritz Blume |
| Director: | Nassir Navab |
| Supervisor: | Martin Groher |
| Type: | SEP |
| Status: | finished |
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