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Dr.-Ing. Jan-Niklas Voigt-Antons


Jan-Niklas Voigt-Antons joined the Telekom Innovation Laboratories as a research scientist in January 2009 and is working there since 2014 as a senior research scientist. He received his diploma in psychology in 2008 from the Technische Universität Darmstadt, Germany, a Doctor-of-Engineering degree in 2014 from the Technische Universität Berlin, Germany and has been doing research at the Quality and Usability Lab at the Technische Universität (TU) Berlin, since. His research interests are in Quality-of-Experience evaluation and its physiological correlates with an emphasis on media transmissions and human-machine-interaction, including neural processing of multimodal interaction. During summer 2012 he was visiting researcher at MuSAE Lab (INRS-EMT), Canada where he examined neural correlates of quality perception for complex speech signals. In spring 2014 he was visiting researcher at the department of psychology of NTNU, Norway where he examined neural correlates of audiovisual asynchrony.

QULab research group: Quality, User Experience, Augmented and Virtual Reality

Research Topics: 

• Multimedia Experience (Usability evaluation methods, Quality-of-Experience evaluation physiological measures)

• Interaction Design (Adaptive software, data mining, sensor and behavioural data)

Current projects:


Measuring of immersive media experience

Exergaming in virtual reality

DemTab - Tabletgestützte ambulante Versorgung von Menschen mit Demenz

VoiceAdapt - Adaptives Sprachtraining für ältere Menschen mit Aphasie

OurPuppet - Pflegeunterstützung mit einer interaktiven Puppe für informell Pflegende

Past projects:

PflegeTab - Technik für mehr Lebensqualität trotz Pflegebedürftigkeit bei Demenz (GKV)

Quality of Mobile Gaming

Bernstein Focus Neurotechnology - Berlin (BFNT - B)


Affective Computing
Study Project Quality & Usability (6/9 CP)


Current thesis offers of our lab can be found here. Please contact me via email if you are interested in doing a thesis supervised by me.


Current job offers of our lab can be found here


+49 30 8353 58 377


Technische Univertistät Berlin
Quality and Usability Lab
Telekom Innovation Laboratories
Ernst-Reuter-Platz 7
10587 Berlin, Germany


Did You Notice It?—How Can We Predict the Subjective Detection of Video Quality Changes From Eye Movements?
Zitatschlüssel radun2017a
Autor Radun, Jenni and Nuutinen, Mikko and Antons, Jan-Niklas and Arndt, Sebastian
Seiten 37–47
Jahr 2017
ISSN 1932-4553
DOI 10.1109/JSTSP.2016.2607696
Adresse Piscataway, NJ
Journal IEEE Journal of Selected Topics in Signal Processing
Jahrgang 11
Nummer 1
Monat feb
Notiz Print, Online
Verlag IEEE
Wie herausgegeben Fullpaper
Zusammenfassung In the case of videos, the measurement of subjective detection of quality degradation usually needs observers to report the detection. However, if this detection could be automatically deduced by nonintrusive means, viewing would not be disturbed. This study examined how the subjective detection of quality degradation can be seen from eye movements, both in terms of group averages as well as from cases of single viewing times. In the experiment, the subjects were given the task of detecting local quality degradation in a video and reporting its significance to the quality of a video. The results of group averages showed that detection of the degraded area changed the viewing strategy from a search with short fixation to an evaluation with long fixations; most importantly, once the evaluation phase had begun, fixations concentrated on a smaller area than in the search phase. The change in eye movements was due to detection and not the quality level. The change in task was also seen in the eye movement measurements from single viewings, the spatial entropy of fixations being the best predictor of subjective detection, with a prediction accuracy rate of 78%. The combination of a temporal change in saccade amplitude and fixation duration averages also predicted detection in single viewing cases, with an accuracy of 68% The study discusses the use of eye movement measurements in video quality estimation and demonstrates that it is possible to predict subjective perception based on the stage of the task.
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