Human Computer Interaction

Finished Thesis Topics

If you are interested in writing a thesis (in German or English) in the scope of one of our research topics, just come talk to us.

List of already finished thesis topics

01.09.2020

A Deep Learning Approach for Expertise Classification using Saccade Behavior

  • Eye movements reflect the cognitive advantage of experts over novices in a domain specific task. Current literature focuses on fixations but leaves out saccades. This research investigates the gaze behavior of dentistry students and expert dentists viewing orthopantomograms (OPTs). All proposed Long Short-Term Memory (LSTM) models were able to distinguish expert and novice gaze behavior by saccade features above guess chance, with the best performing feature having an accuracy of 77.1%. The results provide further evidence for the holistic model of image perception, which proposes that experts initially analyze an image globally, and then proceed with a focal analysis. Further, our results show that saccade features are important to understand expert gaze behavior, and therefore should get integrated into current theories on expertise.

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01.01.2020

Manipulating Yarbus. Online adaptive feedback for scanpath redirection

  • Alfred L. Yarbus investigated eye movement patterns in the 1960s and discovered that top-down contextual clues affect our gaze behavior. With further development of Bailey’s subtle gaze direction method, we investigated whether gaze behavior can be manipulated using adaptive gaze guidance. Trough manipulating salient, visual features in an image, gaze can be guided. Although we did not succeed in significantly manipulating gaze behavior, we developed a stable software for manipulating gaze online. Considering our suggested improvements, it may be possible to manipulate the gaze behavior with adaptive gaze guidance to a certain extent.

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01.01.2020

Differences in attention in near vs. far hand conditions during propaganda viewing

  • The propaganda images used during the active time of the Nationalsozialistische Deutsche Arbeiterpartei (NSDAP), were one of the most influential images used to promote a certain ideology. In modern times these images seem outdated. However, do these propaganda images still influence our perception of Adolf Hitler and his ideology? Using eye tracking, we analyzed the attention distribution of people touching these pictures to find influences of the “near-hand phenomenon”, which explains a more sympathetic affect towards people we touch. It was found that the near-hand viewing condition leads to lower viewing duration and higher number of fixations, indicating a tendency to devote more attention to the images when touching them than compared to the control group.

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10.07.2019

Vein extraction and eye rotation determination

The first step is setting up an recording environment with fixed subject position. This environment is used for data acquisition with predefined head rotations of the subjects. Based on this data an algorithm has to be developed measuring the eyeball rotation of the subject. The resulting angle is then compared and validated based on the head rotation.

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10.07.2019

EyeTrace CUDA extesion

EyeTrace is a software for gaze data visualization and analysis. Due to the increasing amount of data these visualizations need more computation time. In this thesis existing visualizations should be implemented using CUDA for GPU computations. Additionally this includes a data storage model making it possible to shift the data between the GPU and the host computer. Due to the fact that nowadays not all computers have a CUDA capable card the modul should also allow CPU computations. This should be determined automatically by the module.

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10.07.2019

Ein Dashboard für Eyetrace

Die Eyetrace Software bietet eine Vielzahl an Visualisierungsmöglchkeiten für Eye-Tracking Daten. In diesem Projekt soll eine grafisch ansprechende Übersicht über die momentan ins Programm geladenen Daten erzeugt werden.

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10.07.2019

3D Eyeball generation based on vein motion

The first step is robust feature extraction. This can be done using SURF, SIFT, BRISK or MSER features if sufficient. Those features have to be mapped on features found in consecutive images. Based on the displacement a 3D model has to be computed. This model is used afterwards for gaze position estimation.

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