Available Student and Research Projects
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===External Links=== | ===External Links=== | ||
* [http://www.hadleyweb.pwp.blueyonder.co.uk/ CombineZ] | * [http://www.hadleyweb.pwp.blueyonder.co.uk/ CombineZ] | ||
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==Automated photo stitching== | ==Automated photo stitching== | ||
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Also see [[Panorama Viewer|panorama viewer]]. | Also see [[Panorama Viewer|panorama viewer]]. | ||
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* [http://qtpfsgui.sourceforge.net/ HDR workflow with Qtpfsgui] to create HDR images and tonemapping | * [http://qtpfsgui.sourceforge.net/ HDR workflow with Qtpfsgui] to create HDR images and tonemapping | ||
* [http://wiki.panotools.org/HDR_workflow_with_hugin HDR workflow with hugin] to create HDR panoramas | * [http://wiki.panotools.org/HDR_workflow_with_hugin HDR workflow with hugin] to create HDR panoramas | ||
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+ | ==Micro-Manipulation== | ||
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==See Also== | ==See Also== |
Revision as of 17:08, 8 June 2007
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 cross-platform 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
- Scripting using the dynamically-typed object-oriented programming language Ruby
Project areas
Stitching for microscopes
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
Automated photo stitching
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
<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>
- Improve the correspondences using 2D cross-correlation (roll-angle will assumed to be low).
- (Re)implement the panotools-solver preferably in Ruby. Use given correspondences to optimize camera-parameters: rotations, common focal length.
- Adopt existing method for removing fringes (transitions/blending)
Optional:
- Automatically find correspondences
- Optimize more camera-parameters (distortion,...)
Also see panorama viewer.
External Links
- Photo stitching software PTGUI
- Rodriguez Matrix
- Panorama Tools software suite (mirror of Helmut Dersch's former web-page)
- Hugin
- Depth of focus for panorama tools
- Autostitch (commercial)
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 at least 3 degrees-of-freedom problem.
- Demonstrate algorithm on real object.
Optional
- Extend RANSAC implementation to more degrees-of-freedom problem (maybe use line- and point-features)
HDR imaging
Merging pre-aligned 8-bit colour photos into a High dynamic range image will be of high importance as long as low-cost HDR-cameras are not available for the consumer market.
Premise
- A pre-aligned exposure-series of pictures
To Do
- Detect over- and undersaturated colour-components
- Estimate camera sensivity
- Merge images into a single HDR image
Optional:
- Map to reasonably realistic-looking low-range image
See Also
- Wikipedia page on HDR
- HDR images at flickr.com
- OpenEXR library
- HDR workflow with Qtpfsgui to create HDR images and tonemapping
- HDR workflow with hugin to create HDR panoramas