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Student Projects

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Displays Book (free image material)

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Spatial Augmented Reality Book (free ebook)

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VIOSO smartprojecting

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The Flagship Publication of the IEEE Computer Society

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The Caleydo Project

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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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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.

Learning to be a Depth Sensor

Based on Microsoft’s work Learning to be a Depth Camera, we want to investigate if a classification approach (e.g., using regression forests) enables depth estimation of objects being located in front of our novel thin-film image sensor, LumiConSense (see video). The goal of this work is to sense rough distances of known objects based on training and classification.

Topics: machine perception, computer vision, sensors, classification, AI, C++, Matlab
Supervision: Alexander Koppelhuber, Oliver Bimber
Contact: alexander.koppelhuber(/\t)
Type: BSc Practicum, BSc Thesis, MSc Practicum, MSc Thesis

Flight Recommender

Large online databases ( exist that store thousands of glider and para-glider flight tracks every year. They contain information about flight paths, speeds, altitudes, and climb rates. In addition, weather maps of the flight day are linked to the corresponding flight information in form of images. The goal of this project is to implement an image retrieval system that, for a given new weather map, finds (based on image retrieval) the best match in the history of a flight online database. The idea is that days in history with similar weather conditions might allow to recommend similar flight routes.

Topics: image retrieval, computer vision, image processing, pattern matching, Java
Supervision: Clemens Birklbauer, Oliver Bimber
Contact: oliver.bimber(/\t)
Type: BSc Practicum, BSc Thesis, MSc Practicum, MSc 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
Supervision: Samuel Gratzl, Marc Streit
Contact: samuel.gratzl(/\t)
Type: BSc Practicum, BSc Thesis, MSc Practicum, MSc Thesis

Visualizing the Evolution of Cloud Computing Networks

With the high demand for online services such as remote storage and processing power cloud computing networks become more and more important. However, it is difficult for administrators to monitor and optimize such networks. The problem is that the infrastructure as well as the traffic stream are changing over time, making it hard to understand the impact of changes in the design of the cloud infrastructure. The goal of this project is to develop a visualization technique that allows cloud administrators to analyze such topological changes in the context of traffic patterns over time. Seeing the evolution of the network will help users to understand the outcome of changes in the network and also to further optimize the design of the cloud network. The project will be implemented as a web application based on D3.js.

Topics: visualization, visual analytics, networking, cloud computing, live data streaming, D3.js
Supervision: Holger Stitz, Marc Streit
Contact: holger.stitz(/\t)
Type: BSc Practicum, BSc Thesis, MSc Practicum, MSc Thesis

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