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TU Berlin

Inhalt des Dokuments

Alexander Manecke

Lupe

Research Field:

Usability

Research Topics:

  • Connected Home
  • Home automation
  • Smart Meetering
Biography:Alexander Manecke joined Deutsche Telekom Laboratories in 2006 and currently he is working as a research assistant (Wissenschaftlicher Mitarbeiter) at the Quality and Usability Lab of Deutsche Telekom Laboratories, TU-Berlin. He studied computer science at Freie Universität Berlin and has received a diploma in computer science.Address:Quality and Usability LabDeutsche Telekom LaboratoriesTU BerlinWinterfeldstr. 21D-10787 Berlin, Germany
Telefon:
+49 30 8353 58536   E-Mail:

Publications

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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