Available Student and Research Projects
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\begin{pmatrix}m_{1}\\m_{2}\\f\end{pmatrix} | \begin{pmatrix}m_{1}\\m_{2}\\f\end{pmatrix} | ||
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| − | * | + | * (Re)implement the solver using [http://www.boost.org/libs/numeric/ublas/doc/index.htm boost::ublas] and [http://vision.eng.shu.ac.uk/jan/mimas/docs/group__lapack.html Mimas-lapack] |
Contact [[User:Engjw|Jan Wedekind]] for a project in this area. | Contact [[User:Engjw|Jan Wedekind]] for a project in this area. | ||
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===External Links=== | ===External Links=== | ||
* [http://www.ptgui.com/ Photo stitching software PTGUI] | * [http://www.ptgui.com/ Photo stitching software PTGUI] | ||
Revision as of 16:13, 6 November 2006
Contents |
Student Projects
We always offer projects to motivated students (first degree, Masters of Science, ERASMUS student, ...). If you are interested in doing a project in computer vision, let us know. Here is a description of ongoing research areas to give you an idea of possible projects. You can also suggest a research topic yourself.
If you work with us, you can learn a lot of skills which are relevant for a career as a software developer:
- Computer Vision, Signal processing, Robotics
- Linear Algebra, Analysis
- Software Engineering
We are using state-of-the-art platform-independent software tools:
- Source-code documentation with
doxygen
- Cross-platform user-interfaces with
Qt. You can develop full-featured GUI-software which runs under 
GNU/Linux, 
Microsoft Windows, and 
MacOS!
- Platform-independent
Standard Template Library
- Platform-independent
Boost Library
Project areas
Stitching for microscopes
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Premise
- A microscope-video of an object being moved in x-, and y-direction (parallel to the focussed plane)
- Later a microscope-video of an object being moved in x-, y-, and z-direction (i.e. including depth changes)
To Do
- Generate stitched image from the input-video (linear complexity desirable) without feedback from microscope-drive
- Cross-compare images to avoid a drift of the estimated shift
- Later provide extended depth of field by maximising a focus measure.
See Also
External Links
Contact Jan Wedekind for a project in this area.
Automated photo stitching
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Premise
- A set of images taken with the same camera-settings (aperture, exposure time, focal length) and center of projection but different viewing directions (mainly yaw, pitch)
- Manually selected correspondences.
To Do
- Improve the correspondences using 2D cross-correlation (roll-angle will assumed to be low).
- Use these correspondences to optimize the parameters (rotations, common focal length, rotation of virtual camera).
- Transform and merge the images into the resulting panorama image.
<math> \lambda\,\begin{pmatrix}m^\prime_{1}\\m^\prime_{2}\\f\end{pmatrix}= \begin{pmatrix}h_{11}&h_{12}&h_{13}\\h_{21}&h_{22}&h_{23}\\h_{31}&h_{32}&h_{33}\end{pmatrix}\, \begin{pmatrix}m_{1}\\m_{2}\\f\end{pmatrix} </math>
- (Re)implement the solver using boost::ublas and Mimas-lapack
Contact Jan Wedekind for a project in this area.
External Links
- Photo stitching software PTGUI
- Rodriguez Matrix
- Panorama Tools software suite
- Hugin
- Depth of focus for panorama tools
Interactive projector-camera interface
Contact Jan Wedekind for a project in this area.
Premise
- A camera is given images of a projected image (or a TFT screen)
- The system already calibrates itself (two-dimensional homography) using projected patterns
To Do
- Improved method for recognition of hand/fingers
- 3D calibration, depth perception using projected patterns or shadows
See Also
External Links
- Multi-Touch Interaction Research
- Magic board project by IIHM
- IBM Research on interactive projector
- A Flexible New Technique for Camera Calibration: Zhengyou Zhang
- E-Chalk
Physics Engine
Contact Jan Wedekind for a project in this area.
Premise
A physics engines is useful for simulating robots and testing computer vision algorithms. The Open Dynamics Engine was used in two projects already.
To Do
The Open Dynamics Engine is not numerically stable. An investigation into numerical algorithms for simulating multiple rigid bodies is required. The rigid bodies can be connected by joints, which are limiting their degrees of freedom.
See Also
External Links
RANSAC
Random sample consensus is a method for object recognition. This project is about recognising macroscopic rigid objects (e.g. household and office articles like cups, stapler, ...
To Do
- Select point-features and a suitable similarity measure
- Implement RANSAC algorithm and apply to 3 and 4 degrees-of-freedom problem.
- Extend RANSAC implementation to 6 degrees-of-freedom problem (maybe use line- and point-features)
- Demonstrate algorithm on real object.
See Also
See Also
- Have a look at Mimas/Software engineering to get a general impression of our working environment.
- Nanorobotics
- I-Swarm
