Reference picture selection using checkerboard pattern for resilient video coding

The improved compression efficiency achieved by the High Efficiency Video Coding (HEVC) standard has the counter-effect of decreasing error resilience in transmission over error-prone channels. To increase the error resilience of HEVC streams, this paper proposes a checkerboard reference picture selection method in order to reduce the prediction mismatch at the decoder in case of frame losses. The proposed approach not only allows to reduce the error propagation at the decoder, but also enhances the quality of reconstructed frames by selectively constraining the choice of reference pictures used for temporal prediction. The underlying approach is to increase the amount of accurate temporal information at the decoder when transmission errors occur, to improve the video quality by using an efficient combination of diverse motion fields. The proposed method compensates for the small loss of coding efficiency at frame loss rates as low as 3%. For a single frame-loss event the proposed method can achieve up to 2 dB of gain in the affected frames and an average quality gain of 0:84 dB for different error prone conditions

1Mbps is enough: video quality and individual idiosyncrasies in multiparty HD video-conferencing

Most video platforms deliver HD video in high bitrate encoding. Modern video-conferencing systems are capable of handling HD streams, but using multiparty conferencing, average internet connections in the home are on their bandwidth limit. For properly managing the encoding bitrate in videoconferencing, we must know what is the minimum bitrate requirement to provide users an acceptable experience, and what is the bitrate level after which QoE saturates?. Most available subjective studies in this area used rather dated technologies. We report on a multiparty study on video quality with HD resolution. We tested different encoding bitrates (256kbs, 1024kbs and 4096kbs) and packet loss rates (0, 0.5%) in groups of 4 participants with a

Reference picture selection using checkerboard pattern for resilient video coding

The improved compression efficiency achieved by the High Efficiency Video Coding (HEVC) standard has the counter-effect of decreasing error resilience in transmission over error-prone channels. To increase the error resilience of HEVC streams, this paper proposes a checkerboard reference picture selection method in order to reduce the prediction mismatch at the decoder in case of frame losses. The proposed approach not only allows to reduce the error propagation at the decoder, but also enhances the quality of reconstructed frames by selectively constraining the choice of reference pictures used for temporal prediction. The underlying approach is to increase the amount of accurate temporal information at the decoder when transmission errors occur, to improve the video quality by using an efficient combination of diverse motion fields. The proposed method compensates for the small loss of coding efficiency at frame loss rates as low as 3%. For a single frame-loss event the proposed method can achieve up to 2 dB of gain in the affected frames and an average quality gain of 0:84 dB for different error prone conditions

Frame Interpolation for Cloud-Based Mobile Video Streaming

© 2016 IEEE. Cloud-based High Definition (HD) video streaming is becoming popular day by day. On one hand, it is important for both end users and large storage servers to store their huge amount of data at different locations and servers. On the other hand, it is becoming a big challenge for network service providers to provide reliable connectivity to the network users. There have been many studies over cloud-based video streaming for Quality of Experience (QoE) for services like YouTube. Packet losses and bit errors are very common in transmission networks, which affect the user feedback over cloud-based media services. To cover up packet losses and bit errors, Error Concealment (EC) techniques are usually applied at the decoder/receiver side to estimate the lost information. This paper proposes a time-efficient and quality-oriented EC method. The proposed method considers H.265/HEVC based intra-encoded videos for the estimation of whole intra-frame loss. The main emphasis in the proposed approach is the recovery of Motion Vectors (MVs) of a lost frame in real-time. To boost-up the search process for the lost MVs, a bigger block size and searching in parallel are both considered. The simulation results clearly show that our proposed method outperforms the traditional Block Matching Algorithm (BMA) by approximately 2.5 dB and Frame Copy (FC) by up to 12 dB at a packet loss rate of 1%, 3%, and 5% with different Quantization Parameters (QPs). The computational time of the proposed approach outperforms the BMA by approximately 1788 seconds

5G-QoE:QoE Modelling for Ultra-HD Video Streaming in 5G Networks

Traffic on future fifth-generation (5G) mobile networks is predicted to be dominated by challenging video applications such as mobile broadcasting, remote surgery and augmented reality, demanding real-time, and ultra-high quality delivery. Two of the main expectations of 5G networks are that they will be able to handle ultra-high-definition (UHD) video streaming and that they will deliver services that meet the requirements of the end user's perceived quality by adopting quality of experience (QoE) aware network management approaches. This paper proposes a 5G-QoE framework to address the QoE modeling for UHD video flows in 5G networks. Particularly, it focuses on providing a QoE prediction model that is both sufficiently accurate and of low enough complexity to be employed as a continuous real-time indicator of the 'health' of video application flows at the scale required in future 5G networks. The model has been developed and implemented as part of the EU 5G PPP SELFNET autonomic management framework, where it provides a primary indicator of the likely perceptual quality of UHD video application flows traversing a realistic multi-tenanted 5G mobile edge network testbed. The proposed 5G-QoE framework has been implemented in the 5G testbed, and the high accuracy of QoE prediction has been validated through comparing the predicted QoE values with not only subjective testing results but also empirical measurements in the testbed. As such, 5G-QoE would enable a holistic video flow self-optimisation system employing the cutting-edge Scalable H.265 video encoding to transmit UHD video applications in a QoE-aware manner

Impact of media-related SIFs on QoE for H.265/HEVC video streaming

Long term evolution (LTE) is the fastest-deployed mobile broadband technology driven by demand for improved user experience. It has distinguished itself compared to other mobile broadband technologies in its ability to handle the growth of video traffic that has become an important part of user’s mobile broadband experience. Growing trend of video consumption implies that that media-related system influence factors (SIFs) should be identified and well-understood in order to determine how they affect the user’s quality of experience (QoE). Therefore, this paper aims to provide a deeper understanding of media-related SIFs and their impact on QoE for video streaming. Experimental study has included two phases, i.e., H.265/ high efficiency video coding (HEVC) coded video streaming emulation over LTE network and end-user survey for collecting mean opinion score (MOS). Results obtained from statistical analysis imply that there exists strong and statistically significant impact of individual media-related SIFs and their interaction on QoE for video streaming

Hierarchical-p reference picture selection based error resilient video coding framework for high efficiency video coding transmission applications

In this paper, a new reference picture selection (RPS) is proposed for a high efficiency video coding (HEVC) framework. In recent studies, HEVC has been shown to be sensitive to packet error which is unavoidable in transmission applications especially for wireless networks. RPS is an effective error resilient technique for video transmission systems where a feedback channel with short round trip delay time is available. However, its procedure cannot directly apply to the HEVC framework and thus this paper expands it. In RPS, error propagation can still happen during round trip delay time. To alleviate the effect of error propagation for better quality, the proposed algorithm considers both the RPS technique and the region-based intra mode selection method by using some novel features of HEVC. Experimental results demonstrate that the proposed method outperforms the hierarchical-P RPS algorithm in terms of PSNR and other metrics. The average PSNR improvement of the proposed algorithm over the reference algorithm under 10% packet error rate is 1.56 dB for 1080p sequences, 2.32 dB for 720p sequences and 1.01 dB for wide video graphics array (WVGA) sequences, respectively. The performance of proposed method is also tested for applications where feedback information is not available. The proposed method shows noticeable improvement for video sequences that contain low or moderate level of motions

The Impact of Network Impairment on Quality of Experience (QoE) in H.265/HEVC Video Streaming

Users of modern portable consumer devices (smartphones, tablets etc.) expect ubiquitous delivery of high quality services, which fully utilise the capabilities of their devices. Video streaming is one of the most widely used yet challenging services for operators to deliver with assured service levels. This challenge is more apparent in wireless networks where bandwidth constraints and packet loss are common. The lower bandwidth requirements of High Efficiency Video Coding (HEVC) provide the potential to enable service providers to deliver high quality video streams in low-bandwidth networks; however, packet loss may result in greater damage in perceived quality given the higher compression ratio. This work considers the delivery of HEVC encoded video streams in impaired network environments and quantifies the effects of network impairment on HEVC video streaming from the perspective of the end user. HEVC encoded streams were transmitted over a test network with both wired and wireless segments that had imperfect communication channels subject to packet loss. Two different error concealment methods were employed to mitigate packet loss and overcome reference decoder robustness issues. The perceptual quality of received video was subjectively assessed by a panel of viewers. Existing subjective studies of HEVC quality have not considered the implications of network impairments. Analysis of results has quantified the effects of packet loss in HEVC on perceptual quality and provided valuable insight into the relative importance of the main factors observed to influence user perception in HEVC streaming. The outputs from this study show the relative importance and relationship between those factors that affect human perception of quality in impaired HEVC encoded video streams. The subjective analysis is supported by comparison with commonly used objective quality measurement techniques. Outputs from this work may be used in the development of quality of experience (QoE) oriented streaming applications for HEVC in loss prone networks