Sencogi spatio-temporal saliency: A new metric for predicting subjective video quality on mobile devices

Abstract

Objective Video Quality Assessment (VQA) is often used to predict users visual perception of video quality. In the literature, the performance evaluation of objective measures is based on benchmark subjective scores of perceived quality. This paper shows the evaluation of an algorithmic measure on videos presented on mobile devices. The VQA measure is called Sencogi Spatio-Temporal Saliency Metric (Sencogi-STSM), and it uses a spatio-temporal saliency to model subjective perception of video quality. Since STSM was previously validated with a subjective test conducted on laptop computers, the goal of this work was to verify whether the measure is able to significantly predict users’ perception of video quality also on mobile devices. Results show that, compared to the standard VQA metrics, only Sencogi-STSM is able to significantly predict subjective DMOS. This paper describes Sencogi-STSM’s biologically plausible model, its performance evaluation and the comparison with the most commonly used objective VQA metrics.