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Assessment of Technical Quality of Online Video Using Visualization in Place of Experience

M Chignell, D Kaya, L Zucherman, J Jiang. Cited by 6

Abstract

This paper introduces a new method to collect subjective ratings of Technical Quality (TQ) in disrupted video (DV). TQ is related to whether or not the video has disruptions such as impairments (re-buffering, perceived as freezing for a period of time followed by resumption of video playback) or failures (where the video playback stops part way through and fails to complete). The assessment method introduced in this paper avoids the confounding effects of content on TQ ratings and reduces the time and effort necessary to run experiments. Actual videos, as stimuli, are replaced with schematic representations of those videos. We ran an experiment with 37 participants to explore the viability of assessing TQ using visualizations instead of actual videos. The experiment had contrasting conditions that compared TQ ratings of actual videos, vs. schematic representations of videos. The results of the experiment showed that, with appropriate training, ratings of TQ made after viewing the visualizations only were similar to TQ ratings made after actually watching videos with corresponding impairments or failures.

Authors: Mark Chignell, Diba Kaya, Leon Zucherman, Jie Jiang

Published in: Proceedings of the Human Factors and Ergonomics Society Annual Meeting (2016)

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