QoE Assessment for Multi-Video Object Based Media

Abstract

Recent multimedia experiences using techniques such as DASH allow the streaming delivery to be adapted to suit network context. Object Based Media (OBM) provides even more flexibility as distinct media objects are streamed and combined based on user preferences, allowing the experience to be personalised for the user. As adaptation can lead to degradation, modelling and measuring Quality of Experience (QoE) are crucial to ensure a perceptibly-optimal user experience. QoE models proposed for DASH include quality-related factors from single video-object streams and hence, are unsuitable for multi-video OBM experiences. In this paper, we propose an objective method to quantify QoE for video-based OBM experiences. Our model provides different strategies to aggregate individual object QoE contributions for different OBM experience genres. We apply our model to a case study and contrast it with the QoE levels obtained using a standard QoE model for DASH.

Differential QoE in Picture-in-Picture Gaming Videos: A Subjective Study

“…Further studies are needed to determine when a player element becomes significant in terms of QoE. The results of this study could be used to improve video compression of Picture-In-Picture gaming videos in scenarios where Perceptual Video Compression (PVC) with Region-Of-Interest (ROI) encoding is applied, or when content is delivered as independent objects, i.e., Object Based Media (OBM) [13].…”