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Displays Book (free ebook)

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Spatial Augmented Reality Book (free ebook)

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Aero Glass

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The Caleydo Project

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VIOSO smartprojecting

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Location - Computer Science Building (S3)

Location of the Institute for Computer Graphics: Computer Science Building (Science Park 3)

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Content

Theses and Practical Courses

The Institute of Computer Graphics continuously supervises students on all levels (BSc, MSc as well as PhD) in computer graphics, computer vision, visual computing, visualization, or related fields. Each student will be individually advised.... continue reading.
Interested and motivated students are invited to contact us at any time during the semester.

Selected Student Work

A selection of the finest student projects can be found here.

Open Theses Topics

The following list of topics is currently available and can be chosen at any time in the semester. The topics are assigned to our main research areas: Light-Field Processing, Transparent and Flexible Image Sensor and Visual Analytics. Topics will be assigned on a first-come, first-served basis. We also welcome own suggestions that are related to visual computing. LaTex templates for theses and practical course reports are available in German and English. If you have general questions regarding doing a thesis at our institute, feel free to contact us.



Inverse Radon Transform Based On Machine-Learning

In computer tomography (CT), measurements are made in Radon space (spatiodirectional projections of X-ray absorptions, called Radon transform). The inverse of Radon transform allows reconstructing the image of the scanned CT slice. Several approaches to inverse Radon transform exist, such as classical tomographic back-projection. In this project, we want to investigate a first machine-learning approach to inverse Radon transform. This research project addresses talented students with an interest in machine learning and medical image procession. It is open to excellent BSc or MSc candidates. Students will learn fundamentals of tomographic image reconstructions, machine learning, and Matlab programming. The student will publish successful research outcome in a scientific journal, such as ScienceDirect). An option to continue this research direction as a PhD student is given.

Topics: machine learning, image processing, image reconstruction, Matlab
Supervision: Oliver Bimber, Alexander Koppelhuber
Contact: oliver.bimber(/\t)jku.at
Type: BSc Practicum, BSc Thesis, MSc Practicum, MSc Thesis



Closed-Loop Feedback Illumination For Light-Field Microscopes

In 2010, we showed that a controlled spatial illumination pattern in light microscopy can improve the visibility of specimens, both when observed directly through the oculars and when imaged with a camera (see paper for details). In contrast to previous microscopy techniques, we pre-modulated the illumination based on the local modulation properties of the specimen itself — in real-time. In this basic research project, excellent students will work on a new microscope prototype (joint development with Stanford University) that uses light fields for recoding and illumination. The goal is to extend the closed-loop feedback illumination technique from 2010 to light fields. The student will publish successful research outcome in a scientific journal, such as ScienceDirect. An option to continue this research direction as a PhD student is given.

Topics: microscopy, light fields, real-time image processing, GPU programming
Supervision: Oliver Bimber, David Schedl
Contact: oliver.bimber(/\t)jku.at
Type: BSc Practicum, BSc Thesis, MSc Practicum, MSc Thesis



Augmented Reality Supported Aerial Navigation

Navigation in private airplanes is approaching first augmented reality solutions, such as AR glasses (http://glass.aero). They live display navigation, traffic, and whether data that is registered with the surrounding environment. The main challenge we are facing is a robust tracking solution to determine the pilot’s head rotation inside the cockpit to compensate for drift of the gyro, compass, and accelerometer sensors integrated inside the glasses. In this project, students will work with Epson’s BT-200 glasses and investigate appropriate adaptations of an existing SLAM tracking solution for flying conditions. Students will learn basics of augmented reality, optical tracking, and Android programming. The system will be frequently evaluated in test flights.

Topics: augmented reality, optical tracking, Android programming
Supervision: Oliver Bimber, Clemens Birklbauer
Contact: oliver.bimber(/\t)jku.at
Type: BSc Practicum, BSc Thesis



Fusing Data Analysis with Data Wrangling

Solving data intensive problems requires users to merge and analyze datasets that come from different sources, in various formats and semantics. The current workflow in visual data analysis is to first import and specify the semantics of the datasets in a standard importer dialog, before moving on to the actual visual analysis. However, when dealing with multiple, heterogeneous datasets the back and forth between data import and analysis results in a disruption of the workflow that hampers the sense making process. The goal of this project is to seamlessly fuse the data import with the data analysis. The project will be implemented in the Caleydo Web framework, which is based on D3.js, JavaScript and Python.

Topics: visualization, visual analytics, big data, D3.js, Python
Supervision: Samuel Gratzl, Marc Streit
Contact: samuel.gratzl(/\t)jku.at
Type: BSc Practicum, BSc Thesis, MSc Practicum, MSc Thesis



Comparative Visualization of Large Tabular Data

Tabular data plays an important role in many different fields, such as biology or computer science. A primary goal of visualization is to let users understand and make sense of the information contained in the tables. However, this task gets difficult if the structure of the tables change over time (rows and/or columns are added and removed), or if the data values itself are altered. Another challenge is to identify identical or similar subsets across multiple tables. The goal of this project is to create a novel visualization technique that allows users to compare large, inhomogeneous tabular data that can also change over time. The project will be implemented in the Caleydo Web framework , which is based on D3.js, JavaScript and Python.

Topics: visualization, multi-dimensional data, web technology, D3.js, Python
Supervision: Holger Stitz, Samuel Gratzl, Marc Streit
Contact: holger.stitz(/\t)jku.at
Type: BSc Practicum, BSc Thesis, MSc Practicum, MSc Thesis
 

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