Estimating Subjective Video Quality while using Mobile Terminal

Abstract

In this paper, we investigate to estimate the subjective video quality of mobile users in a real situation of daily life. We conduct an experiment to collect bio-signals and sensor data from three subjects for a week as well as their contexts by questionnaire, and machine learning algorithms including Random Forest and k-Nearest Neighbor are applied for the estimation. The experimental results show that the subjective video quality is estimated accurately by Random Forest, while the contribution of users’ context is not confirmed. It suggests that the subjective video quality can be well estimated by bio-signals and sensor data of mobile users in a real situation.