Huyen T. T. Tran

An evaluation of quality metrics for 360 videos

360 videos are becoming more and more popular on video streaming platforms. However, a good quality metric for 360 videos is still an open issue. In this work, we investigate both objective and subjective quality metrics for 360 videos. The goals are to understand the perceived quality range provided by existing mobile 360 videos and, especially, to identify appropriate objective quality metrics for 360 video communications. To that end, a subjective test is conducted in this study. Then, the relationship between objective quality and subjective quality is investigated. Especially, ten objective quality measures are computed, considering the coding distortion measurement, cross-format distortion measurement, and end-to-end distortion measurement. It is found that most of the objective quality measures are well correlated with subjective quality. Also, among the evaluated quality measures, PSNR is shown to be the most appropriate for 360 video communications.

A novel quality model for HTTP adaptive streaming

HTTP Adaptive Streaming (HAS) has become a popular trend for multimedia delivery nowadays. Because of throughput variations, video quality strongly fluctuates during a session. Therefore, a main challenge in HAS is how to evaluate the overall video quality of a session. In this paper, we explore the impact of quality variations on the perceptual quality of a video in HAS. We propose to use the histogram of segment quality values and the histogram of quality gradients in a session to model the overall video quality. Subjective test results show that the proposed model can capture the segment quality variations and accurately predict the overall quality of a session.

A subjective study on QoE of 360 video for VR communication

Currently, more and more 360-degree videos (or 360 videos for short) are being provided via the Internet. This kind of videos can render a virtual reality (VR) environment via a head-mounted display (HMD). However, understanding the quality of experience (QoE) of 360 videos is a big challenge because user experience in VR is a very complex phenomenon. In this paper, the QoE of 360 videos is considered in terms of four aspects, namely perceptual quality, presence, acceptability, and cybersickness. Subjective tests are designed to investigate the influences of important factors including encoding parameters, content characteristics, and device types on QoE aspects. In addition, a comparison of perceptual quality and acceptability between VR and non-VR rendering modes, which refer to watching 360 videos with and without using an HMD respectively, is also made in this study. To the best of our knowledge, this is the first study that covers these four QoE aspects and a large number of influence factors.

A Multi-Factor QoE Model for Adaptive Streaming over Mobile Networks

In the context of HTTP Adaptive Streaming (HAS), a main challenge is how to evaluate the quality of experience (QoE) of a session. In general, the QoE of a streaming session is affected by three key factors, namely initial delay, varying perceptual quality, and interruptions. In this paper, in order to investigate the impacts of quality variations and interruptions on the QoE of a session, we propose to use histograms, which represent the frequency distributions of these recurrent factors in a session. The QoE of a session is modeled by pooling the statistics of the recurrent factors and the initial delay. Evaluation results show that the proposed model has a high prediction performance. Especially, the proposed model provides insights into the impacts of different influence factors, thus leading to suggestions to improve the quality of streaming video.

An Evaluation of Screen Content Casting over Mobile and Wireless Networks

Thanks to the availability of many smart devices, displays, and broadband connections, screen casting/sharing has become an important functionality for user devices. Meanwhile, a new video standard called screen content coding (SCC) is going to be issued to support this trend. This paper presents a standard-compliant implementation and evaluation of SCC streaming to mobile devices. The study is targeted at a feasible design and settings for customer devices, supporting both content-generating side and content-consuming side. The evaluation results help to answer how a sending device should generate screen content videos, and how a receiving device could be implemented and adjusted in time-varying environments of mobile networks and wireless home networks. To the best of our knowledge, this is the first evaluation study for SCC casting.

A QoS-adaptive framework for screen sharing over Internet

In this paper, we present a QoS-adaptive framework for screen sharing over heterogeneous networks. Basic requirements and important issues of a screen sharing system are described. For determining optimal video coding parameters, adaptation trajectory is used as the hints in making decisions. Further, experiments are carried out to investigate the trade-off between video bitrate and the buffering delay in time-varying networks.

Real-time quality evaluation of adaptation strategies in VoD streaming

HTTP Adaptive Streaming (HAS) has become a popular trend for multimedia delivery nowadays. Because of throughput variations, video adaptation methods are needed to avoid buffer underflows. In this context, it is also important to evaluate the overall video quality of a session. In this paper, we investigate a quality model that can evaluate a session quality as well as different adaptation strategies in real time. We use the histogram of segment quality values and the histogram of quality gradients in a session to model the overall video quality. Then, our quality model is employed to evaluate, for the first time, the cumulative quality of typical adaptation methods in real time. It is found that, to provide a high quality level, the client should avoid changing versions frequently and drastically.